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Sample records for gene regulatory modules

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

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    Bringas Ricardo

    2008-01-01

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

  2. Conserved gene regulatory module specifies lateral neural borders across bilaterians.

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    Li, Yongbin; Zhao, Di; Horie, Takeo; Chen, Geng; Bao, Hongcun; Chen, Siyu; Liu, Weihong; Horie, Ryoko; Liang, Tao; Dong, Biyu; Feng, Qianqian; Tao, Qinghua; Liu, Xiao

    2017-08-01

    The lateral neural plate border (NPB), the neural part of the vertebrate neural border, is composed of central nervous system (CNS) progenitors and peripheral nervous system (PNS) progenitors. In invertebrates, PNS progenitors are also juxtaposed to the lateral boundary of the CNS. Whether there are conserved molecular mechanisms determining vertebrate and invertebrate lateral neural borders remains unclear. Using single-cell-resolution gene-expression profiling and genetic analysis, we present evidence that orthologs of the NPB specification module specify the invertebrate lateral neural border, which is composed of CNS and PNS progenitors. First, like in vertebrates, the conserved neuroectoderm lateral border specifier Msx/vab-15 specifies lateral neuroblasts in Caenorhabditis elegans Second, orthologs of the vertebrate NPB specification module ( Msx/vab-15 , Pax3/7/pax-3 , and Zic/ref-2 ) are significantly enriched in worm lateral neuroblasts. In addition, like in other bilaterians, the expression domain of Msx/vab-15 is more lateral than those of Pax3/7/pax-3 and Zic/ref- 2 in C. elegans Third, we show that Msx/vab-15 regulates the development of mechanosensory neurons derived from lateral neural progenitors in multiple invertebrate species, including C. elegans , Drosophila melanogaster , and Ciona intestinalis We also identify a novel lateral neural border specifier, ZNF703/tlp-1 , which functions synergistically with Msx/vab- 15 in both C. elegans and Xenopus laevis These data suggest a common origin of the molecular mechanism specifying lateral neural borders across bilaterians.

  3. Reconstruction of gene regulatory modules from RNA silencing of IFN-α modulators: experimental set-up and inference method.

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    Grassi, Angela; Di Camillo, Barbara; Ciccarese, Francesco; Agnusdei, Valentina; Zanovello, Paola; Amadori, Alberto; Finesso, Lorenzo; Indraccolo, Stefano; Toffolo, Gianna Maria

    2016-03-12

    Inference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation. Here, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α (IFN-α) transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level. Detailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation.

  4. Functional evolution of cis-regulatory modules at a homeotic gene in Drosophila.

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    Margaret C W Ho

    2009-11-01

    Full Text Available It is a long-held belief in evolutionary biology that the rate of molecular evolution for a given DNA sequence is inversely related to the level of functional constraint. This belief holds true for the protein-coding homeotic (Hox genes originally discovered in Drosophila melanogaster. Expression of the Hox genes in Drosophila embryos is essential for body patterning and is controlled by an extensive array of cis-regulatory modules (CRMs. How the regulatory modules functionally evolve in different species is not clear. A comparison of the CRMs for the Abdominal-B gene from different Drosophila species reveals relatively low levels of overall sequence conservation. However, embryonic enhancer CRMs from other Drosophila species direct transgenic reporter gene expression in the same spatial and temporal patterns during development as their D. melanogaster orthologs. Bioinformatic analysis reveals the presence of short conserved sequences within defined CRMs, representing gap and pair-rule transcription factor binding sites. One predicted binding site for the gap transcription factor KRUPPEL in the IAB5 CRM was found to be altered in Superabdominal (Sab mutations. In Sab mutant flies, the third abdominal segment is transformed into a copy of the fifth abdominal segment. A model for KRUPPEL-mediated repression at this binding site is presented. These findings challenge our current understanding of the relationship between sequence evolution at the molecular level and functional activity of a CRM. While the overall sequence conservation at Drosophila CRMs is not distinctive from neighboring genomic regions, functionally critical transcription factor binding sites within embryonic enhancer CRMs are highly conserved. These results have implications for understanding mechanisms of gene expression during embryonic development, enhancer function, and the molecular evolution of eukaryotic regulatory modules.

  5. Modulation of dynamic modes by interplay between positive and negative feedback loops in gene regulatory networks

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    Wang, Liu-Suo; Li, Ning-Xi; Chen, Jing-Jia; Zhang, Xiao-Peng; Liu, Feng; Wang, Wei

    2018-04-01

    A positive and a negative feedback loop can induce bistability and oscillation, respectively, in biological networks. Nevertheless, they are frequently interlinked to perform more elaborate functions in many gene regulatory networks. Coupled positive and negative feedback loops may exhibit either oscillation or bistability depending on the intensity of the stimulus in some particular networks. It is less understood how the transition between the two dynamic modes is modulated by the positive and negative feedback loops. We developed an abstract model of such systems, largely based on the core p53 pathway, to explore the mechanism for the transformation of dynamic behaviors. Our results show that enhancing the positive feedback may promote or suppress oscillations depending on the strength of both feedback loops. We found that the system oscillates with low amplitudes in response to a moderate stimulus and switches to the on state upon a strong stimulus. When the positive feedback is activated much later than the negative one in response to a strong stimulus, the system exhibits long-term oscillations before switching to the on state. We explain this intriguing phenomenon using quasistatic approximation. Moreover, early switching to the on state may occur when the system starts from a steady state in the absence of stimuli. The interplay between the positive and negative feedback plays a key role in the transitions between oscillation and bistability. Of note, our conclusions should be applicable only to some specific gene regulatory networks, especially the p53 network, in which both oscillation and bistability exist in response to a certain type of stimulus. Our work also underscores the significance of transient dynamics in determining cellular outcome.

  6. A systems level approach reveals new gene regulatory modules in the developing ear

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    Chen, Jingchen; Tambalo, Monica; Barembaum, Meyer; Ranganathan, Ramya; Simões-Costa, Marcos; Bronner, Marianne E.; Streit, Andrea

    2017-01-01

    The inner ear is a complex vertebrate sense organ, yet it arises from a simple epithelium, the otic placode. Specification towards otic fate requires diverse signals and transcriptional inputs that act sequentially and/or in parallel. Using the chick embryo, we uncover novel genes in the gene regulatory network underlying otic commitment and reveal dynamic changes in gene expression. Functional analysis of selected transcription factors reveals the genetic hierarchy underlying the transition ...

  7. Integrated analysis of microRNA and gene expression profiles reveals a functional regulatory module associated with liver fibrosis.

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    Chen, Wei; Zhao, Wenshan; Yang, Aiting; Xu, Anjian; Wang, Huan; Cong, Min; Liu, Tianhui; Wang, Ping; You, Hong

    2017-12-15

    Liver fibrosis, characterized with the excessive accumulation of extracellular matrix (ECM) proteins, represents the final common pathway of chronic liver inflammation. Ever-increasing evidence indicates microRNAs (miRNAs) dysregulation has important implications in the different stages of liver fibrosis. However, our knowledge of miRNA-gene regulation details pertaining to such disease remains unclear. The publicly available Gene Expression Omnibus (GEO) datasets of patients suffered from cirrhosis were extracted for integrated analysis. Differentially expressed miRNAs (DEMs) and genes (DEGs) were identified using GEO2R web tool. Putative target gene prediction of DEMs was carried out using the intersection of five major algorithms: DIANA-microT, TargetScan, miRanda, PICTAR5 and miRWalk. Functional miRNA-gene regulatory network (FMGRN) was constructed based on the computational target predictions at the sequence level and the inverse expression relationships between DEMs and DEGs. DAVID web server was selected to perform KEGG pathway enrichment analysis. Functional miRNA-gene regulatory module was generated based on the biological interpretation. Internal connections among genes in liver fibrosis-related module were determined using String database. MiRNA-gene regulatory modules related to liver fibrosis were experimentally verified in recombinant human TGFβ1 stimulated and specific miRNA inhibitor treated LX-2 cells. We totally identified 85 and 923 dysregulated miRNAs and genes in liver cirrhosis biopsy samples compared to their normal controls. All evident miRNA-gene pairs were identified and assembled into FMGRN which consisted of 990 regulations between 51 miRNAs and 275 genes, forming two big sub-networks that were defined as down-network and up-network, respectively. KEGG pathway enrichment analysis revealed that up-network was prominently involved in several KEGG pathways, in which "Focal adhesion", "PI3K-Akt signaling pathway" and "ECM

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

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    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. Copyright © 2013 Elsevier Inc. All rights reserved.

  9. The carboxy-terminal domain of Dictyostelium C-module-binding factor is an independent gene regulatory entity.

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    Jörg Lucas

    Full Text Available The C-module-binding factor (CbfA is a multidomain protein that belongs to the family of jumonji-type (JmjC transcription regulators. In the social amoeba Dictyostelium discoideum, CbfA regulates gene expression during the unicellular growth phase and multicellular development. CbfA and a related D. discoideum CbfA-like protein, CbfB, share a paralogous domain arrangement that includes the JmjC domain, presumably a chromatin-remodeling activity, and two zinc finger-like (ZF motifs. On the other hand, the CbfA and CbfB proteins have completely different carboxy-terminal domains, suggesting that the plasticity of such domains may have contributed to the adaptation of the CbfA-like transcription factors to the rapid genome evolution in the dictyostelid clade. To support this hypothesis we performed DNA microarray and real-time RT-PCR measurements and found that CbfA regulates at least 160 genes during the vegetative growth of D. discoideum cells. Functional annotation of these genes revealed that CbfA predominantly controls the expression of gene products involved in housekeeping functions, such as carbohydrate, purine nucleoside/nucleotide, and amino acid metabolism. The CbfA protein displays two different mechanisms of gene regulation. The expression of one set of CbfA-dependent genes requires at least the JmjC/ZF domain of the CbfA protein and thus may depend on chromatin modulation. Regulation of the larger group of genes, however, does not depend on the entire CbfA protein and requires only the carboxy-terminal domain of CbfA (CbfA-CTD. An AT-hook motif located in CbfA-CTD, which is known to mediate DNA binding to A+T-rich sequences in vitro, contributed to CbfA-CTD-dependent gene regulatory functions in vivo.

  10. Regulatory network analysis of Epstein-Barr virus identifies functional modules and hub genes involved in infectious mononucleosis.

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    Poorebrahim, Mansour; Salarian, Ali; Najafi, Saeideh; Abazari, Mohammad Foad; Aleagha, Maryam Nouri; Dadras, Mohammad Nasr; Jazayeri, Seyed Mohammad; Ataei, Atousa; Poortahmasebi, Vahdat

    2017-05-01

    Epstein-Barr virus (EBV) is the most common cause of infectious mononucleosis (IM) and establishes lifetime infection associated with a variety of cancers and autoimmune diseases. The aim of this study was to develop an integrative gene regulatory network (GRN) approach and overlying gene expression data to identify the representative subnetworks for IM and EBV latent infection (LI). After identifying differentially expressed genes (DEGs) in both IM and LI gene expression profiles, functional annotations were applied using gene ontology (GO) and BiNGO tools, and construction of GRNs, topological analysis and identification of modules were carried out using several plugins of Cytoscape. In parallel, a human-EBV GRN was generated using the Hu-Vir database for further analyses. Our analysis revealed that the majority of DEGs in both IM and LI were involved in cell-cycle and DNA repair processes. However, these genes showed a significant negative correlation in the IM and LI states. Furthermore, cyclin-dependent kinase 2 (CDK2) - a hub gene with the highest centrality score - appeared to be the key player in cell cycle regulation in IM disease. The most significant functional modules in the IM and LI states were involved in the regulation of the cell cycle and apoptosis, respectively. Human-EBV network analysis revealed several direct targets of EBV proteins during IM disease. Our study provides an important first report on the response to IM/LI EBV infection in humans. An important aspect of our data was the upregulation of genes associated with cell cycle progression and proliferation.

  11. Histone methylation mediates plasticity of human FOXP3(+) regulatory T cells by modulating signature gene expressions.

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    He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

    2014-03-01

    CD4(+) FOXP3(+) regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4(+) CD25(high) CD127(low/-) Treg cells convert to two subpopulations with distinctive FOXP3(+) and FOXP3(-) phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. © 2013 John Wiley & Sons Ltd.

  12. Histone methylation mediates plasticity of human FOXP3+ regulatory T cells by modulating signature gene expressions

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    He, Haiqi; Ni, Bing; Tian, Yi; Tian, Zhiqiang; Chen, Yanke; Liu, Zhengwen; Yang, Xiaomei; Lv, Yi; Zhang, Yong

    2014-01-01

    CD4+ FOXP3+ regulatory T (Treg) cells constitute a heterogeneous and plastic T-cell lineage that plays a pivotal role in maintaining immune homeostasis and immune tolerance. However, the fate of human Treg cells after loss of FOXP3 expression and the epigenetic mechanisms contributing to such a phenotype switch remain to be fully elucidated. In the current study, we demonstrate that human CD4+ CD25high CD127low/− Treg cells convert to two subpopulations with distinctive FOXP3+ and FOXP3− phenotypes following in vitro culture with anti-CD3/CD28 and interleukin-2. Digital gene expression analysis showed that upon in vitro expansion, human Treg cells down-regulated Treg cell signature genes, such as FOXP3, CTLA4, ICOS, IKZF2 and LRRC32, but up-regulated a set of T helper lineage-associated genes, especially T helper type 2 (Th2)-associated, such as GATA3, GFI1 and IL13. Subsequent chromatin immunoprecipitation-sequencing of these subpopulations yielded genome-wide maps of their H3K4me3 and H3K27me3 profiles. Surprisingly, reprogramming of Treg cells was associated with differential histone modifications, as evidenced by decreased abundance of permissive H3K4me3 within the down-regulated Treg cell signature genes, such as FOXP3, CTLA4 and LRRC32 loci, and increased abundance of H3K4me3 within the Th2-associated genes, such as IL4 and IL5; however, the H3K27me3 modification profile was not significantly different between the two subpopulations. In conclusion, this study revealed that loss of FOXP3 expression from human Treg cells during in vitro expansion can induce reprogramming to a T helper cell phenotype with a gene expression signature dominated by Th2 lineage-associated genes, and that this cell type conversion may be mediated by histone methylation events. PMID:24152290

  13. Novel sequence variations in LAMA2 and SGCG genes modulating cis-acting regulatory elements and RNA secondary structure

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    Olfa Siala

    2010-01-01

    Full Text Available In this study, we detected new sequence variations in LAMA2 and SGCG genes in 5 ethnic populations, and analysed their effect on enhancer composition and mRNA structure. PCR amplification and DNA sequencing were performed and followed by bioinformatics analyses using ESEfinder as well as MFOLD software. We found 3 novel sequence variations in the LAMA2 (c.3174+22_23insAT and c.6085 +12delA and SGCG (c.*102A/C genes. These variations were present in 210 tested healthy controls from Tunisian, Moroccan, Algerian, Lebanese and French populations suggesting that they represent novel polymorphisms within LAMA2 and SGCG genes sequences. ESEfinder showed that the c.*102A/C substitution created a new exon splicing enhancer in the 3'UTR of SGCG genes, whereas the c.6085 +12delA deletion was situated in the base pairing region between LAMA2 mRNA and the U1snRNA spliceosomal components. The RNA structure analyses showed that both variations modulated RNA secondary structure. Our results are suggestive of correlations between mRNA folding and the recruitment of spliceosomal components mediating splicing, including SR proteins. The contribution of common sequence variations to mRNA structural and functional diversity will contribute to a better study of gene expression.

  14. Finding trans-regulatory genes and protein complexes modulating meiotic recombination hotspots of human, mouse and yeast.

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    Wu, Min; Kwoh, Chee-Keong; Li, Xiaoli; Zheng, Jie

    2014-09-11

    The regulatory mechanism of recombination is one of the most fundamental problems in genomics, with wide applications in genome wide association studies (GWAS), birth-defect diseases, molecular evolution, cancer research, etc. Recombination events cluster into short genomic regions called "recombination hotspots". Recently, a zinc finger protein PRDM9 was reported to regulate recombination hotspots in human and mouse genomes. In addition, a 13-mer motif contained in the binding sites of PRDM9 is found to be enriched in human hotspots. However, this 13-mer motif only covers a fraction of hotspots, indicating that PRDM9 is not the only regulator of recombination hotspots. Therefore, the challenge of discovering other regulators of recombination hotspots becomes significant. Furthermore, recombination is a complex process. Hence, multiple proteins acting as machinery, rather than individual proteins, are more likely to carry out this process in a precise and stable manner. Therefore, the extension of the prediction of individual trans-regulators to protein complexes is also highly desired. In this paper, we introduce a pipeline to identify genes and protein complexes associated with recombination hotspots. First, we prioritize proteins associated with hotspots based on their preference of binding to hotspots and coldspots. Second, using the above identified genes as seeds, we apply the Random Walk with Restart algorithm (RWR) to propagate their influences to other proteins in protein-protein interaction (PPI) networks. Hence, many proteins without DNA-binding information will also be assigned a score to implicate their roles in recombination hotspots. Third, we construct sub-PPI networks induced by top genes ranked by RWR for various species (e.g., yeast, human and mouse) and detect protein complexes in those sub-PPI networks. The GO term analysis show that our prioritizing methods and the RWR algorithm are capable of identifying novel genes associated with

  15. Interplay of the modified nucleotide phosphoadenosine 5'-phosphosulfate (PAPS) with global regulatory proteins in Escherichia coli: modulation of cyclic AMP (cAMP)-dependent gene expression and interaction with the HupA regulatory protein.

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    Longo, Francesca; Motta, Sara; Mauri, Pierluigi; Landini, Paolo; Rossi, Elio

    2016-11-25

    In the bacterium Escherichia coli, some intermediates of the sulfate assimilation and cysteine biosynthesis pathway can act as signal molecules and modulate gene expression. In addition to sensing and utilization of sulphur sources, these signaling mechanisms also impact more global cell processes, such as resistance to antimicrobial agents and biofilm formation. In a recent work, we have shown that inactivation of the cysH gene, encoding phosphoadenosine-phosphosulfate (PAPS) reductase, and the consequent increase in intracellular PAPS concentration, strongly affect production of several cell surface-associated structures, enhancing surface adhesion and cell aggregation. In order to identify the molecular mechanism relaying intracellular PAPS concentration to regulation of cell surface-associated structures, we looked for mutations able to suppress the effects of cysH inactivation. We found that mutations in the adenylate cyclase-encoding cyaA gene abolished the effects of PAPS accumulation; consistent with this result, cyclic AMP (cAMP)-dependent gene expression appears to be increased in the cysH mutant. Experiments aimed at the direct identification of proteins interacting with either CysC or CysH, i.e. the PAPS-related proteins APS kinase and PAPS reductase, allowed us to identify several regulators, namely, CspC, CspE, HNS and HupA. Protein-protein interaction between HupA and CysH was confirmed by a bacterial two hybrid system, and inactivation of the hupA gene enhanced the effects of the cysH mutation in terms of production of cell surface-associated factors. Our results indicate that PAPS can modulate different regulatory systems, providing evidence that this molecule acts as a global signal molecule in E. coli. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  16. Statistical significance of cis-regulatory modules

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    Smith Andrew D

    2007-01-01

    Full Text Available Abstract Background It is becoming increasingly important for researchers to be able to scan through large genomic regions for transcription factor binding sites or clusters of binding sites forming cis-regulatory modules. Correspondingly, there has been a push to develop algorithms for the rapid detection and assessment of cis-regulatory modules. While various algorithms for this purpose have been introduced, most are not well suited for rapid, genome scale scanning. Results We introduce methods designed for the detection and statistical evaluation of cis-regulatory modules, modeled as either clusters of individual binding sites or as combinations of sites with constrained organization. In order to determine the statistical significance of module sites, we first need a method to determine the statistical significance of single transcription factor binding site matches. We introduce a straightforward method of estimating the statistical significance of single site matches using a database of known promoters to produce data structures that can be used to estimate p-values for binding site matches. We next introduce a technique to calculate the statistical significance of the arrangement of binding sites within a module using a max-gap model. If the module scanned for has defined organizational parameters, the probability of the module is corrected to account for organizational constraints. The statistical significance of single site matches and the architecture of sites within the module can be combined to provide an overall estimation of statistical significance of cis-regulatory module sites. Conclusion The methods introduced in this paper allow for the detection and statistical evaluation of single transcription factor binding sites and cis-regulatory modules. The features described are implemented in the Search Tool for Occurrences of Regulatory Motifs (STORM and MODSTORM software.

  17. Prediction of tissue-specific cis-regulatory modules using Bayesian networks and regression trees

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    Chen Xiaoyu

    2007-12-01

    Full Text Available Abstract Background In vertebrates, a large part of gene transcriptional regulation is operated by cis-regulatory modules. These modules are believed to be regulating much of the tissue-specificity of gene expression. Results We develop a Bayesian network approach for identifying cis-regulatory modules likely to regulate tissue-specific expression. The network integrates predicted transcription factor binding site information, transcription factor expression data, and target gene expression data. At its core is a regression tree modeling the effect of combinations of transcription factors bound to a module. A new unsupervised EM-like algorithm is developed to learn the parameters of the network, including the regression tree structure. Conclusion Our approach is shown to accurately identify known human liver and erythroid-specific modules. When applied to the prediction of tissue-specific modules in 10 different tissues, the network predicts a number of important transcription factor combinations whose concerted binding is associated to specific expression.

  18. Modulation of cAMP levels by high-fat diet and curcumin and regulatory effects on CD36/FAT scavenger receptor/fatty acids transporter gene expression.

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    Zingg, Jean-Marc; Hasan, Syeda T; Nakagawa, Kiyotaka; Canepa, Elisa; Ricciarelli, Roberta; Villacorta, Luis; Azzi, Angelo; Meydani, Mohsen

    2017-01-02

    Curcumin, a polyphenol from turmeric (Curcuma longa), reduces inflammation, atherosclerosis, and obesity in several animal studies. In Ldlr -/- mice fed a high-fat diet (HFD), curcumin reduces plasma lipid levels, therefore contributing to a lower accumulation of lipids and to reduced expression of fatty acid transport proteins (CD36/FAT, FABP4/aP2) in peritoneal macrophages. In this study, we analyzed the molecular mechanisms by which curcumin (500, 1000, 1500 mg/kg diet, for 4 months) may influence plasma and tissue lipid levels in Ldlr -/- mice fed an HFD. In liver, HFD significantly suppressed cAMP levels, and curcumin restored almost normal levels. Similar trends were observed in adipose tissues, but not in brain, skeletal muscle, spleen, and kidney. Treatment with curcumin increased phosphorylation of CREB in liver, what may play a role in regulatory effects of curcumin in lipid homeostasis. In cell lines, curcumin increased the level of cAMP, activated the transcription factor CREB and the human CD36 promoter via a sequence containing a consensus CREB response element. Regulatory effects of HFD and Cur on gene expression were observed in liver, less in skeletal muscle and not in brain. Since the cAMP/protein kinase A (PKA)/CREB pathway plays an important role in lipid homeostasis, energy expenditure, and thermogenesis by increasing lipolysis and fatty acid β-oxidation, an increase in cAMP levels induced by curcumin may contribute to its hypolipidemic and anti-atherosclerotic effects. © 2016 BioFactors, 43(1):42-53, 2017. © 2016 International Union of Biochemistry and Molecular Biology.

  19. Deconstructing the pluripotency gene regulatory network

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    Li, Mo

    2018-04-04

    Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

  20. Deconstructing the pluripotency gene regulatory network

    KAUST Repository

    Li, Mo; Belmonte, Juan Carlos Izpisua

    2018-01-01

    Pluripotent stem cells can be isolated from embryos or derived by reprogramming. Pluripotency is stabilized by an interconnected network of pluripotency genes that cooperatively regulate gene expression. Here we describe the molecular principles of pluripotency gene function and highlight post-transcriptional controls, particularly those induced by RNA-binding proteins and alternative splicing, as an important regulatory layer of pluripotency. We also discuss heterogeneity in pluripotency regulation, alternative pluripotency states and future directions of pluripotent stem cell research.

  1. Current approaches to gene regulatory network modelling

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    Brazma Alvis

    2007-09-01

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

  2. Computational challenges in modeling gene regulatory events.

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    Pataskar, Abhijeet; Tiwari, Vijay K

    2016-10-19

    Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. Toward this end, computational biology should keep pace with evolving experimental procedures and data availability. This article gives an exemplified account of the current computational challenges in molecular biology.

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

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    Fung, Elizabeth-sharon [Los Alamos National Laboratory

    2008-01-01

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

  4. Sparsity in Model Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Zagorski, M.

    2011-01-01

    We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

  5. rSNPBase 3.0: an updated database of SNP-related regulatory elements, element-gene pairs and SNP-based gene regulatory networks.

    Science.gov (United States)

    Guo, Liyuan; Wang, Jing

    2018-01-04

    Here, we present the updated rSNPBase 3.0 database (http://rsnp3.psych.ac.cn), which provides human SNP-related regulatory elements, element-gene pairs and SNP-based regulatory networks. This database is the updated version of the SNP regulatory annotation database rSNPBase and rVarBase. In comparison to the last two versions, there are both structural and data adjustments in rSNPBase 3.0: (i) The most significant new feature is the expansion of analysis scope from SNP-related regulatory elements to include regulatory element-target gene pairs (E-G pairs), therefore it can provide SNP-based gene regulatory networks. (ii) Web function was modified according to data content and a new network search module is provided in the rSNPBase 3.0 in addition to the previous regulatory SNP (rSNP) search module. The two search modules support data query for detailed information (related-elements, element-gene pairs, and other extended annotations) on specific SNPs and SNP-related graphic networks constructed by interacting transcription factors (TFs), miRNAs and genes. (3) The type of regulatory elements was modified and enriched. To our best knowledge, the updated rSNPBase 3.0 is the first data tool supports SNP functional analysis from a regulatory network prospective, it will provide both a comprehensive understanding and concrete guidance for SNP-related regulatory studies. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. Mutational robustness of gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Aalt D J van Dijk

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

  7. Modulation of gene expression made easy

    DEFF Research Database (Denmark)

    Solem, Christian; Jensen, Peter Ruhdal

    2002-01-01

    A new approach for modulating gene expression, based on randomization of promoter (spacer) sequences, was developed. The method was applied to chromosomal genes in Lactococcus lactis and shown to generate libraries of clones with broad ranges of expression levels of target genes. In one example...... that the method can be applied to modulating the expression of native genes on the chromosome. We constructed a series of strains in which the expression of the las operon, containing the genes pfk, pyk, and ldh, was modulated by integrating a truncated copy of the pfk gene. Importantly, the modulation affected...

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

    Directory of Open Access Journals (Sweden)

    Vipin Narang

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

  9. Finding cis-regulatory modules in Drosophila using phylogenetic hidden Markov models

    DEFF Research Database (Denmark)

    Wong, Wendy S W; Nielsen, Rasmus

    2007-01-01

    MOTIVATION: Finding the regulatory modules for transcription factors binding is an important step in elucidating the complex molecular mechanisms underlying regulation of gene expression. There are numerous methods available for solving this problem, however, very few of them take advantage of th...

  10. The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

    Directory of Open Access Journals (Sweden)

    Frank eEmmert-Streib

    2014-02-01

    Full Text Available 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.

  11. On the role of sparseness in the evolution of modularity in gene regulatory networks.

    Science.gov (United States)

    Espinosa-Soto, Carlos

    2018-05-01

    Modularity is a widespread property in biological systems. It implies that interactions occur mainly within groups of system elements. A modular arrangement facilitates adjustment of one module without perturbing the rest of the system. Therefore, modularity of developmental mechanisms is a major factor for evolvability, the potential to produce beneficial variation from random genetic change. Understanding how modularity evolves in gene regulatory networks, that create the distinct gene activity patterns that characterize different parts of an organism, is key to developmental and evolutionary biology. One hypothesis for the evolution of modules suggests that interactions between some sets of genes become maladaptive when selection favours additional gene activity patterns. The removal of such interactions by selection would result in the formation of modules. A second hypothesis suggests that modularity evolves in response to sparseness, the scarcity of interactions within a system. Here I simulate the evolution of gene regulatory networks and analyse diverse experimentally sustained networks to study the relationship between sparseness and modularity. My results suggest that sparseness alone is neither sufficient nor necessary to explain modularity in gene regulatory networks. However, sparseness amplifies the effects of forms of selection that, like selection for additional gene activity patterns, already produce an increase in modularity. That evolution of new gene activity patterns is frequent across evolution also supports that it is a major factor in the evolution of modularity. That sparseness is widespread across gene regulatory networks indicates that it may have facilitated the evolution of modules in a wide variety of cases.

  12. Simple mathematical models of gene regulatory dynamics

    CERN Document Server

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

    2016-01-01

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

  13. Generic Properties of Random Gene Regulatory Networks.

    Science.gov (United States)

    Li, Zhiyuan; Bianco, Simone; Zhang, Zhaoyang; Tang, Chao

    2013-12-01

    Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties change with network's topological characteristics. In this work, we first investigated these questions in random GRNs with different network sizes, connectivity, fraction of inhibitory links and transcription regulation rules. Then we searched for the core motifs that govern the dynamic behavior of large GRNs. We show that the stability of a random GRN is typically governed by a few embedding motifs of small sizes, and therefore can in general be understood in the context of these short motifs. Our results provide insights for the study and design of genetic networks.

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

    Science.gov (United States)

    Zhu, Mingzhu; Dahmen, Jeremy L; Stacey, Gary; Cheng, Jianlin

    2013-09-22

    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. 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. 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.

  15. A HLA class I cis-regulatory element whose activity can be modulated by hormones.

    Science.gov (United States)

    Sim, B C; Hui, K M

    1994-12-01

    To elucidate the basis of the down-regulation in major histocompatibility complex (MHC) class I gene expression and to identify possible DNA-binding regulatory elements that have the potential to interact with class I MHC genes, we have studied the transcriptional regulation of class I HLA genes in human breast carcinoma cells. A 9 base pair (bp) negative cis-regulatory element (NRE) has been identified using band-shift assays employing DNA sequences derived from the 5'-flanking region of HLA class I genes. This 9-bp element, GTCATGGCG, located within exon I of the HLA class I gene, can potently inhibit the expression of a heterologous thymidine kinase (TK) gene promoter and the HLA enhancer element. Furthermore, this regulatory element can exert its suppressive function in either the sense or anti-sense orientation. More interestingly, NRE can suppress dexamethasone-mediated gene activation in the context of the reported glucocorticoid-responsive element (GRE) in MCF-7 cells but has no influence on the estrogen-mediated transcriptional activation of MCF-7 cells in the context of the reported estrogen-responsive element (ERE). Furthermore, the presence of such a regulatory element within the HLA class I gene whose activity can be modulated by hormones correlates well with our observation that the level of HLA class I gene expression can be down-regulated by hormones in human breast carcinoma cells. Such interactions between negative regulatory elements and specific hormone trans-activators are novel and suggest a versatile form of transcriptional control.

  16. A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

    Directory of Open Access Journals (Sweden)

    Haitao Guo

    2017-01-01

    Full Text Available The discovery of cis-regulatory modules (CRMs is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them.

  17. A New Algorithm for Identifying Cis-Regulatory Modules Based on Hidden Markov Model

    Science.gov (United States)

    2017-01-01

    The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs. We test ComSPS on three benchmark datasets and compare it with five existing methods. Experimental results show that ComSPS performs better than them. PMID:28497059

  18. Gene set-based module discovery in the breast cancer transcriptome

    Directory of Open Access Journals (Sweden)

    Zhang Michael Q

    2009-02-01

    Full Text Available Abstract Background Although microarray-based studies have revealed global view of gene expression in cancer cells, we still have little knowledge about regulatory mechanisms underlying the transcriptome. Several computational methods applied to yeast data have recently succeeded in identifying expression modules, which is defined as co-expressed gene sets under common regulatory mechanisms. However, such module discovery methods are not applied cancer transcriptome data. Results In order to decode oncogenic regulatory programs in cancer cells, we developed a novel module discovery method termed EEM by extending a previously reported module discovery method, and applied it to breast cancer expression data. Starting from seed gene sets prepared based on cis-regulatory elements, ChIP-chip data, and gene locus information, EEM identified 10 principal expression modules in breast cancer based on their expression coherence. Moreover, EEM depicted their activity profiles, which predict regulatory programs in each subtypes of breast tumors. For example, our analysis revealed that the expression module regulated by the Polycomb repressive complex 2 (PRC2 is downregulated in triple negative breast cancers, suggesting similarity of transcriptional programs between stem cells and aggressive breast cancer cells. We also found that the activity of the PRC2 expression module is negatively correlated to the expression of EZH2, a component of PRC2 which belongs to the E2F expression module. E2F-driven EZH2 overexpression may be responsible for the repression of the PRC2 expression modules in triple negative tumors. Furthermore, our network analysis predicts regulatory circuits in breast cancer cells. Conclusion These results demonstrate that the gene set-based module discovery approach is a powerful tool to decode regulatory programs in cancer cells.

  19. A Regulatory Network Analysis of Orphan Genes in Arabidopsis Thaliana

    Science.gov (United States)

    Singh, Pramesh; Chen, Tianlong; Arendsee, Zebulun; Wurtele, Eve S.; Bassler, Kevin E.

    Orphan genes, which are genes unique to each particular species, have recently drawn significant attention for their potential usefulness for organismal robustness. Their origin and regulatory interaction patterns remain largely undiscovered. Recently, methods that use the context likelihood of relatedness to infer a network followed by modularity maximizing community detection algorithms on the inferred network to find the functional structure of regulatory networks were shown to be effective. We apply improved versions of these methods to gene expression data from Arabidopsis thaliana, identify groups (clusters) of interacting genes with related patterns of expression and analyze the structure within those groups. Focusing on clusters that contain orphan genes, we compare the identified clusters to gene ontology (GO) terms, regulons, and pathway designations and analyze their hierarchical structure. We predict new regulatory interactions and unravel the structure of the regulatory interaction patterns of orphan genes. Work supported by the NSF through Grants DMR-1507371 and IOS-1546858.

  20. Evolution of Cis-Regulatory Elements and Regulatory Networks in Duplicated Genes of Arabidopsis.

    Science.gov (United States)

    Arsovski, Andrej A; Pradinuk, Julian; Guo, Xu Qiu; Wang, Sishuo; Adams, Keith L

    2015-12-01

    Plant genomes contain large numbers of duplicated genes that contribute to the evolution of new functions. Following duplication, genes can exhibit divergence in their coding sequence and their expression patterns. Changes in the cis-regulatory element landscape can result in changes in gene expression patterns. High-throughput methods developed recently can identify potential cis-regulatory elements on a genome-wide scale. Here, we use a recent comprehensive data set of DNase I sequencing-identified cis-regulatory binding sites (footprints) at single-base-pair resolution to compare binding sites and network connectivity in duplicated gene pairs in Arabidopsis (Arabidopsis thaliana). We found that duplicated gene pairs vary greatly in their cis-regulatory element architecture, resulting in changes in regulatory network connectivity. Whole-genome duplicates (WGDs) have approximately twice as many footprints in their promoters left by potential regulatory proteins than do tandem duplicates (TDs). The WGDs have a greater average number of footprint differences between paralogs than TDs. The footprints, in turn, result in more regulatory network connections between WGDs and other genes, forming denser, more complex regulatory networks than shown by TDs. When comparing regulatory connections between duplicates, WGDs had more pairs in which the two genes are either partially or fully diverged in their network connections, but fewer genes with no network connections than the TDs. There is evidence of younger TDs and WGDs having fewer unique connections compared with older duplicates. This study provides insights into cis-regulatory element evolution and network divergence in duplicated genes. © 2015 American Society of Plant Biologists. All Rights Reserved.

  1. Transcription factor trapping by RNA in gene regulatory elements.

    Science.gov (United States)

    Sigova, Alla A; Abraham, Brian J; Ji, Xiong; Molinie, Benoit; Hannett, Nancy M; Guo, Yang Eric; Jangi, Mohini; Giallourakis, Cosmas C; Sharp, Phillip A; Young, Richard A

    2015-11-20

    Transcription factors (TFs) bind specific sequences in promoter-proximal and -distal DNA elements to regulate gene transcription. RNA is transcribed from both of these DNA elements, and some DNA binding TFs bind RNA. Hence, RNA transcribed from regulatory elements may contribute to stable TF occupancy at these sites. We show that the ubiquitously expressed TF Yin-Yang 1 (YY1) binds to both gene regulatory elements and their associated RNA species across the entire genome. Reduced transcription of regulatory elements diminishes YY1 occupancy, whereas artificial tethering of RNA enhances YY1 occupancy at these elements. We propose that RNA makes a modest but important contribution to the maintenance of certain TFs at gene regulatory elements and suggest that transcription of regulatory elements produces a positive-feedback loop that contributes to the stability of gene expression programs. Copyright © 2015, American Association for the Advancement of Science.

  2. Evolving chromosomes and gene regulatory networks

    Indian Academy of Sciences (India)

    Aswin

    Genes under H NS control can be. (a) regulated by H NS. (b) regulated by H NS and StpA. Because backup by StpA is partial. Page 19. Gene expression level. H NS regulated xenogenes. Other genes. Page 20 ... recollect: H&NS silences highl transcribable genes. Gene expression level unilateral. Other genes epistatic ...

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

    Science.gov (United States)

    Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

    2017-10-01

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

  4. Global Regulatory Differences for Gene- and Cell-Based Therapies

    DEFF Research Database (Denmark)

    Coppens, Delphi G M; De Bruin, Marie L; Leufkens, Hubert G M

    2017-01-01

    Gene- and cell-based therapies (GCTs) offer potential new treatment options for unmet medical needs. However, the use of conventional regulatory requirements for medicinal products to approve GCTs may impede patient access and therapeutic innovation. Furthermore, requirements differ between...... jurisdictions, complicating the global regulatory landscape. We provide a comparative overview of regulatory requirements for GCT approval in five jurisdictions and hypothesize on the consequences of the observed global differences on patient access and therapeutic innovation....

  5. Robustness and accuracy in sea urchin developmental gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Smadar eBen-Tabou De-Leon

    2016-02-01

    Full Text Available 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. Oct4 targets regulatory nodes to modulate stem cell function.

    Directory of Open Access Journals (Sweden)

    Pearl A Campbell

    2007-06-01

    Full Text Available Stem cells are characterized by two defining features, the ability to self-renew and to differentiate into highly specialized cell types. The POU homeodomain transcription factor Oct4 (Pou5f1 is an essential mediator of the embryonic stem cell state and has been implicated in lineage specific differentiation, adult stem cell identity, and cancer. Recent description of the regulatory networks which maintain 'ES' have highlighted a dual role for Oct4 in the transcriptional activation of genes required to maintain self-renewal and pluripotency while concomitantly repressing genes which facilitate lineage specific differentiation. However, the molecular mechanism by which Oct4 mediates differential activation or repression at these loci to either maintain stem cell identity or facilitate the emergence of alternate transcriptional programs required for the realization of lineage remains to be elucidated. To further investigate Oct4 function, we employed gene expression profiling together with a robust statistical analysis to identify genes highly correlated to Oct4. Gene Ontology analysis to categorize overrepresented genes has led to the identification of themes which may prove essential to stem cell identity, including chromatin structure, nuclear architecture, cell cycle control, DNA repair, and apoptosis. Our experiments have identified previously unappreciated roles for Oct4 for firstly, regulating chromatin structure in a state consistent with self-renewal and pluripotency, and secondly, facilitating the expression of genes that keeps the cell poised to respond to cues that lead to differentiation. Together, these data define the mechanism by which Oct4 orchestrates cellular regulatory pathways to enforce the stem cell state and provides important insight into stem cell function and cancer.

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

    NARCIS (Netherlands)

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

    2008-01-01

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

  8. Semi-supervised prediction of gene regulatory networks using ...

    Indian Academy of Sciences (India)

    2015-09-28

    Sep 28, 2015 ... Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging ... two types of methods differ primarily based on whether ..... negligible, allowing us to draw the qualitative conclusions .... research will be conducted to develop additional biologically.

  9. Learning gene regulatory networks from only positive and unlabeled data

    Directory of Open Access Journals (Sweden)

    Elkan Charles

    2010-05-01

    Full Text Available Abstract Background Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled as a binary classification problem for each pair of genes. A statistical classifier is trained to recognize the relationships between the activation profiles of gene pairs. This approach has been proven to outperform previous unsupervised methods. However, the supervised approach raises open questions. In particular, although known regulatory connections can safely be assumed to be positive training examples, obtaining negative examples is not straightforward, because definite knowledge is typically not available that a given pair of genes do not interact. Results A recent advance in research on data mining is a method capable of learning a classifier from only positive and unlabeled examples, that does not need labeled negative examples. Applied to the reconstruction of gene regulatory networks, we show that this method significantly outperforms the current state of the art of machine learning methods. We assess the new method using both simulated and experimental data, and obtain major performance improvement. Conclusions Compared to unsupervised methods for gene network inference, supervised methods are potentially more accurate, but for training they need a complete set of known regulatory connections. A supervised method that can be trained using only positive and unlabeled data, as presented in this paper, is especially beneficial for the task of inferring gene regulatory networks, because only an incomplete set of known regulatory connections is available in public databases such as RegulonDB, TRRD, KEGG, Transfac, and IPA.

  10. Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

    Directory of Open Access Journals (Sweden)

    Buer Jan

    2004-12-01

    Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

  11. Functional modules by relating protein interaction networks and gene expression.

    Science.gov (United States)

    Tornow, Sabine; Mewes, H W

    2003-11-01

    Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

  12. Challenges for modeling global gene regulatory networks during development: insights from Drosophila.

    Science.gov (United States)

    Wilczynski, Bartek; Furlong, Eileen E M

    2010-04-15

    Development is regulated by dynamic patterns of gene expression, which are orchestrated through the action of complex gene regulatory networks (GRNs). Substantial progress has been made in modeling transcriptional regulation in recent years, including qualitative "coarse-grain" models operating at the gene level to very "fine-grain" quantitative models operating at the biophysical "transcription factor-DNA level". Recent advances in genome-wide studies have revealed an enormous increase in the size and complexity or GRNs. Even relatively simple developmental processes can involve hundreds of regulatory molecules, with extensive interconnectivity and cooperative regulation. This leads to an explosion in the number of regulatory functions, effectively impeding Boolean-based qualitative modeling approaches. At the same time, the lack of information on the biophysical properties for the majority of transcription factors within a global network restricts quantitative approaches. In this review, we explore the current challenges in moving from modeling medium scale well-characterized networks to more poorly characterized global networks. We suggest to integrate coarse- and find-grain approaches to model gene regulatory networks in cis. We focus on two very well-studied examples from Drosophila, which likely represent typical developmental regulatory modules across metazoans. Copyright (c) 2009 Elsevier Inc. All rights reserved.

  13. TransDetect Identifies a New Regulatory Module Controlling Phosphate Accumulation.

    Science.gov (United States)

    Pal, Sikander; Kisko, Mushtak; Dubos, Christian; Lacombe, Benoit; Berthomieu, Pierre; Krouk, Gabriel; Rouached, Hatem

    2017-10-01

    Identifying transcription factor (TFs) cooperation controlling target gene expression is still an arduous challenge. The accuracy of current methods at genome scale significantly drops with the increase in number of genes, which limits their applicability to more complex genomes, like animals and plants. Here, we developed an algorithm, TransDetect, able to predict TF combinations controlling the expression level of a given gene. TransDetect was used to identify novel TF modules regulating the expression of Arabidopsis ( Arabidopsis thaliana ) phosphate transporter PHO1;H3 comprising MYB15, MYB84, bHLH35, and ICE1. These TFs were confirmed to interact between themselves and with the PHO1;H3 promoter. Phenotypic and genetic analyses of TF mutants enable the organization of these four TFs and PHO1;H3 in a new gene regulatory network controlling phosphate accumulation in zinc-dependent manner. This demonstrates the potential of TransDetect to extract directionality in nondynamic transcriptomes and to provide a blueprint to identify gene regulatory network involved in a given biological process. © 2017 American Society of Plant Biologists. All Rights Reserved.

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  15. Gene Regulation, Modulation, and Their Applications in Gene Expression Data Analysis

    Directory of Open Access Journals (Sweden)

    Mario Flores

    2013-01-01

    Full Text Available Common microarray and next-generation sequencing data analysis concentrate on tumor subtype classification, marker detection, and transcriptional regulation discovery during biological processes by exploring the correlated gene expression patterns and their shared functions. Genetic regulatory network (GRN based approaches have been employed in many large studies in order to scrutinize for dysregulation and potential treatment controls. In addition to gene regulation and network construction, the concept of the network modulator that has significant systemic impact has been proposed, and detection algorithms have been developed in past years. Here we provide a unified mathematic description of these methods, followed with a brief survey of these modulator identification algorithms. As an early attempt to extend the concept to new RNA regulation mechanism, competitive endogenous RNA (ceRNA, into a modulator framework, we provide two applications to illustrate the network construction, modulation effect, and the preliminary finding from these networks. Those methods we surveyed and developed are used to dissect the regulated network under different modulators. Not limit to these, the concept of “modulation” can adapt to various biological mechanisms to discover the novel gene regulation mechanisms.

  16. Innate immune activity conditions the effect of regulatory variants upon monocyte gene expression.

    Science.gov (United States)

    Fairfax, Benjamin P; Humburg, Peter; Makino, Seiko; Naranbhai, Vivek; Wong, Daniel; Lau, Evelyn; Jostins, Luke; Plant, Katharine; Andrews, Robert; McGee, Chris; Knight, Julian C

    2014-03-07

    To systematically investigate the impact of immune stimulation upon regulatory variant activity, we exposed primary monocytes from 432 healthy Europeans to interferon-γ (IFN-γ) or differing durations of lipopolysaccharide and mapped expression quantitative trait loci (eQTLs). More than half of cis-eQTLs identified, involving hundreds of genes and associated pathways, are detected specifically in stimulated monocytes. Induced innate immune activity reveals multiple master regulatory trans-eQTLs including the major histocompatibility complex (MHC), coding variants altering enzyme and receptor function, an IFN-β cytokine network showing temporal specificity, and an interferon regulatory factor 2 (IRF2) transcription factor-modulated network. Induced eQTL are significantly enriched for genome-wide association study loci, identifying context-specific associations to putative causal genes including CARD9, ATM, and IRF8. Thus, applying pathophysiologically relevant immune stimuli assists resolution of functional genetic variants.

  17. Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

    Science.gov (United States)

    Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

    2014-01-01

    Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

  18. Sequence-based model of gap gene regulatory network.

    Science.gov (United States)

    Kozlov, Konstantin; Gursky, Vitaly; Kulakovskiy, Ivan; Samsonova, Maria

    2014-01-01

    The detailed analysis of transcriptional regulation is crucially important for understanding biological processes. The gap gene network in Drosophila attracts large interest among researches studying mechanisms of transcriptional regulation. It implements the most upstream regulatory layer of the segmentation gene network. The knowledge of molecular mechanisms involved in gap gene regulation is far less complete than that of genetics of the system. Mathematical modeling goes beyond insights gained by genetics and molecular approaches. It allows us to reconstruct wild-type gene expression patterns in silico, infer underlying regulatory mechanism and prove its sufficiency. We developed a new model that provides a dynamical description of gap gene regulatory systems, using detailed DNA-based information, as well as spatial transcription factor concentration data at varying time points. We showed that this model correctly reproduces gap gene expression patterns in wild type embryos and is able to predict gap expression patterns in Kr mutants and four reporter constructs. We used four-fold cross validation test and fitting to random dataset to validate the model and proof its sufficiency in data description. The identifiability analysis showed that most model parameters are well identifiable. We reconstructed the gap gene network topology and studied the impact of individual transcription factor binding sites on the model output. We measured this impact by calculating the site regulatory weight as a normalized difference between the residual sum of squares error for the set of all annotated sites and for the set with the site of interest excluded. The reconstructed topology of the gap gene network is in agreement with previous modeling results and data from literature. We showed that 1) the regulatory weights of transcription factor binding sites show very weak correlation with their PWM score; 2) sites with low regulatory weight are important for the model output; 3

  19. Gene regulatory mechanisms in infected fish

    DEFF Research Database (Denmark)

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

    2011-01-01

    molecules produced by the eukaryotic cell is used to program the RNA Induced Silencing Complex (RISC) for cleavage of specific mRNA transcripts and/or translational repression in the cytoplasm or even chromatin methylation in the nucleus. All processes leading to silencing of the target gene. MicroRNAs (or...... differentiation. Thus the expression of these miRNAs might be steered by different mechanisms in different cell types and have different roles in terms of the genes they target in different cell types. Thus gene regulation and function is better looked upon as a web of interactions. Data from zebrafish studies...

  20. Gene regulatory networks elucidating huanglongbing disease mechanisms.

    Directory of Open Access Journals (Sweden)

    Federico Martinelli

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

  1. Lmx1b-targeted cis-regulatory modules involved in limb dorsalization.

    Science.gov (United States)

    Haro, Endika; Watson, Billy A; Feenstra, Jennifer M; Tegeler, Luke; Pira, Charmaine U; Mohan, Subburaman; Oberg, Kerby C

    2017-06-01

    Lmx1b is a homeodomain transcription factor responsible for limb dorsalization. Despite striking double-ventral (loss-of-function) and double-dorsal (gain-of-function) limb phenotypes, no direct gene targets in the limb have been confirmed. To determine direct targets, we performed a chromatin immunoprecipitation against Lmx1b in mouse limbs at embryonic day 12.5 followed by next-generation sequencing (ChIP-seq). Nearly 84% ( n =617) of the Lmx1b-bound genomic intervals (LBIs) identified overlap with chromatin regulatory marks indicative of potential cis -regulatory modules (PCRMs). In addition, 73 LBIs mapped to CRMs that are known to be active during limb development. We compared Lmx1b-bound PCRMs with genes regulated by Lmx1b and found 292 PCRMs within 1 Mb of 254 Lmx1b-regulated genes. Gene ontological analysis suggests that Lmx1b targets extracellular matrix production, bone/joint formation, axonal guidance, vascular development, cell proliferation and cell movement. We validated the functional activity of a PCRM associated with joint-related Gdf5 that provides a mechanism for Lmx1b-mediated joint modification and a PCRM associated with Lmx1b that suggests a role in autoregulation. This is the first report to describe genome-wide Lmx1b binding during limb development, directly linking Lmx1b to targets that accomplish limb dorsalization. © 2017. Published by The Company of Biologists Ltd.

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

    Science.gov (United States)

    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

  3. PReMod: a database of genome-wide mammalian cis-regulatory module predictions.

    Science.gov (United States)

    Ferretti, Vincent; Poitras, Christian; Bergeron, Dominique; Coulombe, Benoit; Robert, François; Blanchette, Mathieu

    2007-01-01

    We describe PReMod, a new database of genome-wide cis-regulatory module (CRM) predictions for both the human and the mouse genomes. The prediction algorithm, described previously in Blanchette et al. (2006) Genome Res., 16, 656-668, exploits the fact that many known CRMs are made of clusters of phylogenetically conserved and repeated transcription factors (TF) binding sites. Contrary to other existing databases, PReMod is not restricted to modules located proximal to genes, but in fact mostly contains distal predicted CRMs (pCRMs). Through its web interface, PReMod allows users to (i) identify pCRMs around a gene of interest; (ii) identify pCRMs that have binding sites for a given TF (or a set of TFs) or (iii) download the entire dataset for local analyses. Queries can also be refined by filtering for specific chromosomal regions, for specific regions relative to genes or for the presence of CpG islands. The output includes information about the binding sites predicted within the selected pCRMs, and a graphical display of their distribution within the pCRMs. It also provides a visual depiction of the chromosomal context of the selected pCRMs in terms of neighboring pCRMs and genes, all of which are linked to the UCSC Genome Browser and the NCBI. PReMod: http://genomequebec.mcgill.ca/PReMod.

  4. Identification of miRNA-mRNA regulatory modules by exploring collective group relationships.

    Science.gov (United States)

    Masud Karim, S M; Liu, Lin; Le, Thuc Duy; Li, Jiuyong

    2016-01-11

    microRNAs (miRNAs) play an essential role in the post-transcriptional gene regulation in plants and animals. They regulate a wide range of biological processes by targeting messenger RNAs (mRNAs). Evidence suggests that miRNAs and mRNAs interact collectively in gene regulatory networks. The collective relationships between groups of miRNAs and groups of mRNAs may be more readily interpreted than those between individual miRNAs and mRNAs, and thus are useful for gaining insight into gene regulation and cell functions. Several computational approaches have been developed to discover miRNA-mRNA regulatory modules (MMRMs) with a common aim to elucidate miRNA-mRNA regulatory relationships. However, most existing methods do not consider the collective relationships between a group of miRNAs and the group of targeted mRNAs in the process of discovering MMRMs. Our aim is to develop a framework to discover MMRMs and reveal miRNA-mRNA regulatory relationships from the heterogeneous expression data based on the collective relationships. We propose DIscovering COllective group RElationships (DICORE), an effective computational framework for revealing miRNA-mRNA regulatory relationships. We utilize the notation of collective group relationships to build the computational framework. The method computes the collaboration scores of the miRNAs and mRNAs on the basis of their interactions with mRNAs and miRNAs, respectively. Then it determines the groups of miRNAs and groups of mRNAs separately based on their respective collaboration scores. Next, it calculates the strength of the collective relationship between each pair of miRNA group and mRNA group using canonical correlation analysis, and the group pairs with significant canonical correlations are considered as the MMRMs. We applied this method to three gene expression datasets, and validated the computational discoveries. Analysis of the results demonstrates that a large portion of the regulatory relationships discovered by

  5. SELANSI: a toolbox for simulation of stochastic gene regulatory networks.

    Science.gov (United States)

    Pájaro, Manuel; Otero-Muras, Irene; Vázquez, Carlos; Alonso, Antonio A

    2018-03-01

    Gene regulation is inherently stochastic. In many applications concerning Systems and Synthetic Biology such as the reverse engineering and the de novo design of genetic circuits, stochastic effects (yet potentially crucial) are often neglected due to the high computational cost of stochastic simulations. With advances in these fields there is an increasing need of tools providing accurate approximations of the stochastic dynamics of gene regulatory networks (GRNs) with reduced computational effort. This work presents SELANSI (SEmi-LAgrangian SImulation of GRNs), a software toolbox for the simulation of stochastic multidimensional gene regulatory networks. SELANSI exploits intrinsic structural properties of gene regulatory networks to accurately approximate the corresponding Chemical Master Equation with a partial integral differential equation that is solved by a semi-lagrangian method with high efficiency. Networks under consideration might involve multiple genes with self and cross regulations, in which genes can be regulated by different transcription factors. Moreover, the validity of the method is not restricted to a particular type of kinetics. The tool offers total flexibility regarding network topology, kinetics and parameterization, as well as simulation options. SELANSI runs under the MATLAB environment, and is available under GPLv3 license at https://sites.google.com/view/selansi. antonio@iim.csic.es. © The Author(s) 2017. Published by Oxford University Press.

  6. Interrogating the topological robustness of gene regulatory circuits by randomization.

    Directory of Open Access Journals (Sweden)

    Bin Huang

    2017-03-01

    Full Text Available One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE, for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT, from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression.

  7. Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

    Science.gov (United States)

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

    2017-10-01

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

  8. Portrait of Candida Species Biofilm Regulatory Network Genes.

    Science.gov (United States)

    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. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Modeling stochasticity and robustness in gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

    2009-06-15

    Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

  10. KIRMES: kernel-based identification of regulatory modules in euchromatic sequences.

    Science.gov (United States)

    Schultheiss, Sebastian J; Busch, Wolfgang; Lohmann, Jan U; Kohlbacher, Oliver; Rätsch, Gunnar

    2009-08-15

    Understanding transcriptional regulation is one of the main challenges in computational biology. An important problem is the identification of transcription factor (TF) binding sites in promoter regions of potential TF target genes. It is typically approached by position weight matrix-based motif identification algorithms using Gibbs sampling, or heuristics to extend seed oligos. Such algorithms succeed in identifying single, relatively well-conserved binding sites, but tend to fail when it comes to the identification of combinations of several degenerate binding sites, as those often found in cis-regulatory modules. We propose a new algorithm that combines the benefits of existing motif finding with the ones of support vector machines (SVMs) to find degenerate motifs in order to improve the modeling of regulatory modules. In experiments on microarray data from Arabidopsis thaliana, we were able to show that the newly developed strategy significantly improves the recognition of TF targets. The python source code (open source-licensed under GPL), the data for the experiments and a Galaxy-based web service are available at http://www.fml.mpg.de/raetsch/suppl/kirmes/.

  11. Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

    Science.gov (United States)

    Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

    2017-10-03

    With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

  12. Synchronous versus asynchronous modeling of gene regulatory networks.

    Science.gov (United States)

    Garg, Abhishek; Di Cara, Alessandro; Xenarios, Ioannis; Mendoza, Luis; De Micheli, Giovanni

    2008-09-01

    In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

  13. Singular Perturbation Analysis and Gene Regulatory Networks with Delay

    Science.gov (United States)

    Shlykova, Irina; Ponosov, Arcady

    2009-09-01

    There are different ways of how to model gene regulatory networks. Differential equations allow for a detailed description of the network's dynamics and provide an explicit model of the gene concentration changes over time. Production and relative degradation rate functions used in such models depend on the vector of steeply sloped threshold functions which characterize the activity of genes. The most popular example of the threshold functions comes from the Boolean network approach, where the threshold functions are given by step functions. The system of differential equations becomes then piecewise linear. The dynamics of this system can be described very easily between the thresholds, but not in the switching domains. For instance this approach fails to analyze stationary points of the system and to define continuous solutions in the switching domains. These problems were studied in [2], [3], but the proposed model did not take into account a time delay in cellular systems. However, analysis of real gene expression data shows a considerable number of time-delayed interactions suggesting that time delay is essential in gene regulation. Therefore, delays may have a great effect on the dynamics of the system presenting one of the critical factors that should be considered in reconstruction of gene regulatory networks. The goal of this work is to apply the singular perturbation analysis to certain systems with delay and to obtain an analog of Tikhonov's theorem, which provides sufficient conditions for constracting the limit system in the delay case.

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

    DEFF Research Database (Denmark)

    Bojanovic, Klara

    evolved numerous mechanisms to controlgene expression in response to specific environmental signals. In addition to two-component systems, small regulatory RNAs (sRNAs) have emerged as major regulators of gene expression. The majority of sRNAs bind to mRNA and regulate their expression. They often have...... multiple targets and are incorporated into large regulatory networks and the RNA chaper one Hfq in many cases facilitates interactions between sRNAs and their targets. Some sRNAs also act by binding to protein targets and sequestering their function. In this PhD thesis we investigated the transcriptional....... Detailed insights into the mechanisms through which P. putida responds to different stress conditions and increased understanding of bacterial adaptation in natural and industrial settings were gained. Additionally, we identified genome-wide transcription start sites, andmany regulatory RNA elements...

  15. Establishing neural crest identity: a gene regulatory recipe

    Science.gov (United States)

    Simões-Costa, Marcos; Bronner, Marianne E.

    2015-01-01

    The neural crest is a stem/progenitor cell population that contributes to a wide variety of derivatives, including sensory and autonomic ganglia, cartilage and bone of the face and pigment cells of the skin. Unique to vertebrate embryos, it has served as an excellent model system for the study of cell behavior and identity owing to its multipotency, motility and ability to form a broad array of cell types. Neural crest development is thought to be controlled by a suite of transcriptional and epigenetic inputs arranged hierarchically in a gene regulatory network. Here, we examine neural crest development from a gene regulatory perspective and discuss how the underlying genetic circuitry results in the features that define this unique cell population. PMID:25564621

  16. On the dynamics of a gene regulatory network

    International Nuclear Information System (INIS)

    Grammaticos, B; Carstea, A S; Ramani, A

    2006-01-01

    We examine the dynamics of a network of genes focusing on a periodic chain of genes, of arbitrary length. We show that within a given class of sigmoids representing the equilibrium probability of the binding of the RNA polymerase to the core promoter, the system possesses a single stable fixed point. By slightly modifying the sigmoid, introducing 'stiffer' forms, we show that it is possible to find network configurations exhibiting bistable behaviour. Our results do not depend crucially on the length of the chain considered: calculations with finite chains lead to similar results. However, a realistic study of regulatory genetic networks would require the consideration of more complex topologies and interactions

  17. Syndromes associated with Homo sapiens pol II regulatory genes.

    Science.gov (United States)

    Bina, M; Demmon, S; Pares-Matos, E I

    2000-01-01

    The molecular basis of human characteristics is an intriguing but an unresolved problem. Human characteristics cover a broad spectrum, from the obvious to the abstract. Obvious characteristics may include morphological features such as height, shape, and facial form. Abstract characteristics may be hidden in processes that are controlled by hormones and the human brain. In this review we examine exaggerated characteristics presented as syndromes. Specifically, we focus on human genes that encode transcription factors to examine morphological, immunological, and hormonal anomalies that result from deletion, insertion, or mutation of genes that regulate transcription by RNA polymerase II (the Pol II genes). A close analysis of abnormal phenotypes can give clues into how sequence variations in regulatory genes and changes in transcriptional control may give rise to characteristics defined as complex traits.

  18. Inferring the conservative causal core of gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Emmert-Streib Frank

    2010-09-01

    Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

  19. Inferring the conservative causal core of gene regulatory networks.

    Science.gov (United States)

    Altay, Gökmen; Emmert-Streib, Frank

    2010-09-28

    Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. In this paper, we introduce a novel gene regulatory network inference (GRNI) algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.

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

    LENUS (Irish Health Repository)

    2010-01-01

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

  1. Alignment and prediction of cis-regulatory modules based on a probabilistic model of evolution.

    Directory of Open Access Journals (Sweden)

    Xin He

    2009-03-01

    Full Text Available Cross-species comparison has emerged as a powerful paradigm for predicting cis-regulatory modules (CRMs and understanding their evolution. The comparison requires reliable sequence alignment, which remains a challenging task for less conserved noncoding sequences. Furthermore, the existing models of DNA sequence evolution generally do not explicitly treat the special properties of CRM sequences. To address these limitations, we propose a model of CRM evolution that captures different modes of evolution of functional transcription factor binding sites (TFBSs and the background sequences. A particularly novel aspect of our work is a probabilistic model of gains and losses of TFBSs, a process being recognized as an important part of regulatory sequence evolution. We present a computational framework that uses this model to solve the problems of CRM alignment and prediction. Our alignment method is similar to existing methods of statistical alignment but uses the conserved binding sites to improve alignment. Our CRM prediction method deals with the inherent uncertainties of binding site annotations and sequence alignment in a probabilistic framework. In simulated as well as real data, we demonstrate that our program is able to improve both alignment and prediction of CRM sequences over several state-of-the-art methods. Finally, we used alignments produced by our program to study binding site conservation in genome-wide binding data of key transcription factors in the Drosophila blastoderm, with two intriguing results: (i the factor-bound sequences are under strong evolutionary constraints even if their neighboring genes are not expressed in the blastoderm and (ii binding sites in distal bound sequences (relative to transcription start sites tend to be more conserved than those in proximal regions. Our approach is implemented as software, EMMA (Evolutionary Model-based cis-regulatory Module Analysis, ready to be applied in a broad biological context.

  2. An integrative approach to inferring biologically meaningful gene modules

    Directory of Open Access Journals (Sweden)

    Wang Kai

    2011-07-01

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

  3. The capacity for multistability in small gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Grotewold Erich

    2009-09-01

    Full Text Available Abstract Background Recent years have seen a dramatic increase in the use of mathematical modeling to gain insight into gene regulatory network behavior across many different organisms. In particular, there has been considerable interest in using mathematical tools to understand how multistable regulatory networks may contribute to developmental processes such as cell fate determination. Indeed, such a network may subserve the formation of unicellular leaf hairs (trichomes in the model plant Arabidopsis thaliana. Results In order to investigate the capacity of small gene regulatory networks to generate multiple equilibria, we present a chemical reaction network (CRN-based modeling formalism and describe a number of methods for CRN analysis in a parameter-free context. These methods are compared and applied to a full set of one-component subnetworks, as well as a large random sample from 40,680 similarly constructed two-component subnetworks. We find that positive feedback and cooperativity mediated by transcription factor (TF dimerization is a requirement for one-component subnetwork bistability. For subnetworks with two components, the presence of these processes increases the probability that a randomly sampled subnetwork will exhibit multiple equilibria, although we find several examples of bistable two-component subnetworks that do not involve cooperative TF-promoter binding. In the specific case of epidermal differentiation in Arabidopsis, dimerization of the GL3-GL1 complex and cooperative sequential binding of GL3-GL1 to the CPC promoter are each independently sufficient for bistability. Conclusion Computational methods utilizing CRN-specific theorems to rule out bistability in small gene regulatory networks are far superior to techniques generally applicable to deterministic ODE systems. Using these methods to conduct an unbiased survey of parameter-free deterministic models of small networks, and the Arabidopsis epidermal cell

  4. The Reconstruction and Analysis of Gene Regulatory Networks.

    Science.gov (United States)

    Zheng, Guangyong; Huang, Tao

    2018-01-01

    In post-genomic era, an important task is to explore the function of individual biological molecules (i.e., gene, noncoding RNA, protein, metabolite) and their organization in living cells. For this end, gene regulatory networks (GRNs) are constructed to show relationship between biological molecules, in which the vertices of network denote biological molecules and the edges of network present connection between nodes (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). Biologists can understand not only the function of biological molecules but also the organization of components of living cells through interpreting the GRNs, since a gene regulatory network is a comprehensively physiological map of living cells and reflects influence of genetic and epigenetic factors (Strogatz, Nature 410:268-276, 2001; Bray, Science 301:1864-1865, 2003). In this paper, we will review the inference methods of GRN reconstruction and analysis approaches of network structure. As a powerful tool for studying complex diseases and biological processes, the applications of the network method in pathway analysis and disease gene identification will be introduced.

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

    Directory of Open Access Journals (Sweden)

    Kari Y Lam

    2016-12-01

    Full Text Available 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.

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

    Science.gov (United States)

    Ridgway, Anthony; Agbanyo, Francisca; Wang, Jian; Rosu-Myles, Michael

    2015-01-01

    Health Canada regulates gene therapy products and many cell therapy products as biological drugs under the Canadian Food and Drugs Act and its attendant regulations. Cellular products that meet certain criteria, including minimal manipulation and homologous use, may be subjected to a standards-based approach under the Safety of Human Cells, Tissues and Organs for Transplantation Regulations. The manufacture and clinical testing of cell and gene therapy products (CGTPs) presents many challenges beyond those for protein biologics. Cells cannot be subjected to pathogen removal or inactivation procedures and must frequently be administered shortly after final formulation. Viral vector design and manufacturing control are critically important to overall product quality and linked to safety and efficacy in patients through concerns such as replication competence, vector integration, and vector shedding. In addition, for many CGTPs, the value of nonclinical studies is largely limited to providing proof of concept, and the first meaningful data relating to appropriate dosing, safety parameters, and validity of surrogate or true determinants of efficacy must come from carefully designed clinical trials in patients. Addressing these numerous challenges requires application of various risk mitigation strategies and meeting regulatory expectations specifically adapted to the product types. Regulatory cooperation and harmonisation at an international level are essential for progress in the development and commercialisation of these products. However, particularly in the area of cell therapy, new regulatory paradigms may be needed to harness the benefits of clinical progress in situations where the resources and motivation to pursue a typical drug product approval pathway may be lacking.

  7. Overexpression of maize anthocyanin regulatory gene Lc affects rice fertility.

    Science.gov (United States)

    Li, Yuan; Zhang, Tao; Shen, Zhong-Wei; Xu, Yu; Li, Jian-Yue

    2013-01-01

    Seventeen independent transgenic rice plants with the maize anthocyanin regulatory gene Lc under control of the CaMV 35S promoter were obtained and verified by molecular identification. Ten plants showed red spikelets during early development of florets, and the degenerate florets were still red after heading. Additionally, these plants exhibited intense pigmentation on the surface of the anther and the bottom of the ovary. They were unable to properly bloom and were completely sterile. Following pollination with normal pollen, these plants yielded red caryopses but did not mature normally. QRT-PCR analysis indicated that mRNA accumulation of the CHS-like gene encoding a chalcone synthase-related protein was increased significantly in the sterile plant. This is the first report to suggest that upregulation of the CHS gene expression may result in rice sterility and affect the normal development of rice seeds.

  8. Inferring Gene Regulatory Networks Using Conditional Regulation Pattern to Guide Candidate Genes.

    Directory of Open Access Journals (Sweden)

    Fei Xiao

    Full Text Available Combining path consistency (PC algorithms with conditional mutual information (CMI are widely used in reconstruction of gene regulatory networks. CMI has many advantages over Pearson correlation coefficient in measuring non-linear dependence to infer gene regulatory networks. It can also discriminate the direct regulations from indirect ones. However, it is still a challenge to select the conditional genes in an optimal way, which affects the performance and computation complexity of the PC algorithm. In this study, we develop a novel conditional mutual information-based algorithm, namely RPNI (Regulation Pattern based Network Inference, to infer gene regulatory networks. For conditional gene selection, we define the co-regulation pattern, indirect-regulation pattern and mixture-regulation pattern as three candidate patterns to guide the selection of candidate genes. To demonstrate the potential of our algorithm, we apply it to gene expression data from DREAM challenge. Experimental results show that RPNI outperforms existing conditional mutual information-based methods in both accuracy and time complexity for different sizes of gene samples. Furthermore, the robustness of our algorithm is demonstrated by noisy interference analysis using different types of noise.

  9. Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

    Science.gov (United States)

    Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.

    2017-01-01

    Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552

  10. Validation of Skeletal Muscle cis-Regulatory Module Predictions Reveals Nucleotide Composition Bias in Functional Enhancers

    Science.gov (United States)

    Kwon, Andrew T.; Chou, Alice Yi; Arenillas, David J.; Wasserman, Wyeth W.

    2011-01-01

    We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs) using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions. PMID:22144875

  11. Validation of skeletal muscle cis-regulatory module predictions reveals nucleotide composition bias in functional enhancers.

    Directory of Open Access Journals (Sweden)

    Andrew T Kwon

    2011-12-01

    Full Text Available We performed a genome-wide scan for muscle-specific cis-regulatory modules (CRMs using three computational prediction programs. Based on the predictions, 339 candidate CRMs were tested in cell culture with NIH3T3 fibroblasts and C2C12 myoblasts for capacity to direct selective reporter gene expression to differentiated C2C12 myotubes. A subset of 19 CRMs validated as functional in the assay. The rate of predictive success reveals striking limitations of computational regulatory sequence analysis methods for CRM discovery. Motif-based methods performed no better than predictions based only on sequence conservation. Analysis of the properties of the functional sequences relative to inactive sequences identifies nucleotide sequence composition can be an important characteristic to incorporate in future methods for improved predictive specificity. Muscle-related TFBSs predicted within the functional sequences display greater sequence conservation than non-TFBS flanking regions. Comparison with recent MyoD and histone modification ChIP-Seq data supports the validity of the functional regions.

  12. cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.

    Science.gov (United States)

    Yang, Tzu-Hsien; Wang, Chung-Ching; Hung, Po-Cheng; Wu, Wei-Sheng

    2014-01-01

    Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms

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

    KAUST Repository

    Fujii, Chisato; Kuwahara, Hiroyuki; Yu, Ge; Guo, Lili; Gao, Xin

    2016-01-01

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

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

    KAUST Repository

    Fujii, Chisato

    2016-08-25

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

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

    Science.gov (United States)

    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. Copyright © 2013 Elsevier B.V. All rights reserved.

  16. Ground rules of the pluripotency gene regulatory network.

    KAUST Repository

    Li, Mo

    2017-01-03

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

  17. Ground rules of the pluripotency gene regulatory network.

    KAUST Repository

    Li, Mo; Belmonte, Juan Carlos Izpisua

    2017-01-01

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

  18. Directed partial correlation: inferring large-scale gene regulatory network through induced topology disruptions.

    Directory of Open Access Journals (Sweden)

    Yinyin Yuan

    Full Text Available 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/.

  19. Predicting tissue specific cis-regulatory modules in the human genome using pairs of co-occurring motifs

    Directory of Open Access Journals (Sweden)

    Girgis Hani Z

    2012-02-01

    Full Text Available Abstract Background Researchers seeking to unlock the genetic basis of human physiology and diseases have been studying gene transcription regulation. The temporal and spatial patterns of gene expression are controlled by mainly non-coding elements known as cis-regulatory modules (CRMs and epigenetic factors. CRMs modulating related genes share the regulatory signature which consists of transcription factor (TF binding sites (TFBSs. Identifying such CRMs is a challenging problem due to the prohibitive number of sequence sets that need to be analyzed. Results We formulated the challenge as a supervised classification problem even though experimentally validated CRMs were not required. Our efforts resulted in a software system named CrmMiner. The system mines for CRMs in the vicinity of related genes. CrmMiner requires two sets of sequences: a mixed set and a control set. Sequences in the vicinity of the related genes comprise the mixed set, whereas the control set includes random genomic sequences. CrmMiner assumes that a large percentage of the mixed set is made of background sequences that do not include CRMs. The system identifies pairs of closely located motifs representing vertebrate TFBSs that are enriched in the training mixed set consisting of 50% of the gene loci. In addition, CrmMiner selects a group of the enriched pairs to represent the tissue-specific regulatory signature. The mixed and the control sets are searched for candidate sequences that include any of the selected pairs. Next, an optimal Bayesian classifier is used to distinguish candidates found in the mixed set from their control counterparts. Our study proposes 62 tissue-specific regulatory signatures and putative CRMs for different human tissues and cell types. These signatures consist of assortments of ubiquitously expressed TFs and tissue-specific TFs. Under controlled settings, CrmMiner identified known CRMs in noisy sets up to 1:25 signal-to-noise ratio. CrmMiner was

  20. Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

    OpenAIRE

    Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

    2009-01-01

    Abstract Background Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori assumptions about the interactions, which all simulate the observed patterns. It is important to analyze the properties of the circuits. Findings We have analyzed the simulated gene expression ...

  1. DREAM (Downstream Regulatory Element Antagonist Modulator contributes to synaptic depression and contextual fear memory

    Directory of Open Access Journals (Sweden)

    Wu Long-Jun

    2010-01-01

    Full Text Available Abstract The downstream regulatory element antagonist modulator (DREAM, a multifunctional Ca2+-binding protein, binds specifically to DNA and several nucleoproteins regulating gene expression and with proteins outside the nucleus to regulate membrane excitability or calcium homeostasis. DREAM is highly expressed in the central nervous system including the hippocampus and cortex; however, the roles of DREAM in hippocampal synaptic transmission and plasticity have not been investigated. Taking advantage of transgenic mice overexpressing a Ca2+-insensitive DREAM mutant (TgDREAM, we used integrative methods including electrophysiology, biochemistry, immunostaining, and behavior tests to study the function of DREAM in synaptic transmission, long-term plasticity and fear memory in hippocampal CA1 region. We found that NMDA receptor but not AMPA receptor-mediated current was decreased in TgDREAM mice. Moreover, synaptic plasticity, such as long-term depression (LTD but not long-term potentiation (LTP, was impaired in TgDREAM mice. Biochemical experiments found that DREAM interacts with PSD-95 and may inhibit NMDA receptor function through this interaction. Contextual fear memory was significantly impaired in TgDREAM mice. By contrast, sensory responses to noxious stimuli were not affected. Our results demonstrate that DREAM plays a novel role in postsynaptic modulation of the NMDA receptor, and contributes to synaptic plasticity and behavioral memory.

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

    KAUST Repository

    Fujii, Chisato

    2015-04-16

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

  3. Predictive modelling of gene expression from transcriptional regulatory elements.

    Science.gov (United States)

    Budden, David M; Hurley, Daniel G; Crampin, Edmund J

    2015-07-01

    Predictive modelling of gene expression provides a powerful framework for exploring the regulatory logic underpinning transcriptional regulation. Recent studies have demonstrated the utility of such models in identifying dysregulation of gene and miRNA expression associated with abnormal patterns of transcription factor (TF) binding or nucleosomal histone modifications (HMs). Despite the growing popularity of such approaches, a comparative review of the various modelling algorithms and feature extraction methods is lacking. We define and compare three methods of quantifying pairwise gene-TF/HM interactions and discuss their suitability for integrating the heterogeneous chromatin immunoprecipitation (ChIP)-seq binding patterns exhibited by TFs and HMs. We then construct log-linear and ϵ-support vector regression models from various mouse embryonic stem cell (mESC) and human lymphoblastoid (GM12878) data sets, considering both ChIP-seq- and position weight matrix- (PWM)-derived in silico TF-binding. The two algorithms are evaluated both in terms of their modelling prediction accuracy and ability to identify the established regulatory roles of individual TFs and HMs. Our results demonstrate that TF-binding and HMs are highly predictive of gene expression as measured by mRNA transcript abundance, irrespective of algorithm or cell type selection and considering both ChIP-seq and PWM-derived TF-binding. As we encourage other researchers to explore and develop these results, our framework is implemented using open-source software and made available as a preconfigured bootable virtual environment. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

  4. Inferring Drosophila gap gene regulatory network: Pattern analysis of simulated gene expression profiles and stability analysis

    NARCIS (Netherlands)

    Fomekong-Nanfack, Y.; Postma, M.; Kaandorp, J.A.

    2009-01-01

    Background: Inference of gene regulatory networks (GRNs) requires accurate data, a method to simulate the expression patterns and an efficient optimization algorithm to estimate the unknown parameters. Using this approach it is possible to obtain alternative circuits without making any a priori

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

    Science.gov (United States)

    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. © 2016. Published by The Company of Biologists Ltd.

  6. Cis-regulatory element based targeted gene finding: genome-wide identification of abscisic acid- and abiotic stress-responsive genes in Arabidopsis thaliana.

    Science.gov (United States)

    Zhang, Weixiong; Ruan, Jianhua; Ho, Tuan-Hua David; You, Youngsook; Yu, Taotao; Quatrano, Ralph S

    2005-07-15

    A fundamental problem of computational genomics is identifying the genes that respond to certain endogenous cues and environmental stimuli. This problem can be referred to as targeted gene finding. Since gene regulation is mainly determined by the binding of transcription factors and cis-regulatory DNA sequences, most existing gene annotation methods, which exploit the conservation of open reading frames, are not effective in finding target genes. A viable approach to targeted gene finding is to exploit the cis-regulatory elements that are known to be responsible for the transcription of target genes. Given such cis-elements, putative target genes whose promoters contain the elements can be identified. As a case study, we apply the above approach to predict the genes in model plant Arabidopsis thaliana which are inducible by a phytohormone, abscisic acid (ABA), and abiotic stress, such as drought, cold and salinity. We first construct and analyze two ABA specific cis-elements, ABA-responsive element (ABRE) and its coupling element (CE), in A.thaliana, based on their conservation in rice and other cereal plants. We then use the ABRE-CE module to identify putative ABA-responsive genes in A.thaliana. Based on RT-PCR verification and the results from literature, this method has an accuracy rate of 67.5% for the top 40 predictions. The cis-element based targeted gene finding approach is expected to be widely applicable since a large number of cis-elements in many species are available.

  7. Computational and molecular dissection of an X-box cis-Regulatory module

    OpenAIRE

    Warrington, Timothy Burton

    2015-01-01

    Ciliopathies are a class of human diseases marked by dysfunction of the cellular organelle, cilia. While many of the molecular components that make up cilia have been identified and studied, comparatively little is understood about the transcriptional regulation of genes encoding these components. The conserved transcription factor Regulatory Factor X (RFX)/DAF-19, which acts through binding to the cis-regulatory motif known as X-box, has been shown to regulate ciliary genes in many animals f...

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

    Science.gov (United States)

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

    2012-05-01

    The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration. © 2012 WILEY PERIODICALS, INC.

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

    Science.gov (United States)

    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

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

    Directory of Open Access Journals (Sweden)

    Qiang Zhang

    2007-03-01

    Full Text Available 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

  11. Cis-regulatory control of the nuclear receptor Coup-TF gene in the sea urchin Paracentrotus lividus embryo.

    Directory of Open Access Journals (Sweden)

    Lamprini G Kalampoki

    Full Text Available Coup-TF, an orphan member of the nuclear receptor super family, has a fundamental role in the development of metazoan embryos. The study of the gene's regulatory circuit in the sea urchin embryo will facilitate the placement of this transcription factor in the well-studied embryonic Gene Regulatory Network (GRN. The Paracentrotus lividus Coup-TF gene (PlCoup-TF is expressed throughout embryonic development preferentially in the oral ectoderm of the gastrula and the ciliary band of the pluteus stage. Two overlapping λ genomic clones, containing three exons and upstream sequences of PlCoup-TF, were isolated from a genomic library. The transcription initiation site was determined and 5' deletions and individual segments of a 1930 bp upstream region were placed ahead of a GFP reporter cassette and injected into fertilized P.lividus eggs. Module a (-532 to -232, was necessary and sufficient to confer ciliary band expression to the reporter. Comparison of P.lividus and Strongylocentrotus purpuratus upstream Coup-TF sequences, revealed considerable conservation, but none within module a. 5' and internal deletions into module a, defined a smaller region that confers ciliary band specific expression. Putative regulatory cis-acting elements (RE1, RE2 and RE3 within module a, were specifically bound by proteins in sea urchin embryonic nuclear extracts. Site-specific mutagenesis of these elements resulted in loss of reporter activity (RE1 or ectopic expression (RE2, RE3. It is proposed that sea urchin transcription factors, which bind these three regulatory sites, are necessary for spatial and quantitative regulation of the PlCoup-TF gene at pluteus stage sea urchin embryos. These findings lead to the future identification of these factors and to the hierarchical positioning of PlCoup-TF within the embryonic GRN.

  12. Identification of co-expression gene networks, regulatory genes and pathways for obesity based on adipose tissue RNA Sequencing in a porcine model

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Cirera Salicio, Susanna; Zhernakova, Daria V.

    2014-01-01

    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...... (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 ... 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...

  13. Gene Therapy With Regulatory T Cells: A Beneficial Alliance

    Directory of Open Access Journals (Sweden)

    Moanaro Biswas

    2018-03-01

    Full Text Available Gene therapy aims to replace a defective or a deficient protein at therapeutic or curative levels. Improved vector designs have enhanced safety, efficacy, and delivery, with potential for lasting treatment. However, innate and adaptive immune responses to the viral vector and transgene product remain obstacles to the establishment of therapeutic efficacy. It is widely accepted that endogenous regulatory T cells (Tregs are critical for tolerance induction to the transgene product and in some cases the viral vector. There are two basic strategies to harness the suppressive ability of Tregs: in vivo induction of adaptive Tregs specific to the introduced gene product and concurrent administration of autologous, ex vivo expanded Tregs. The latter may be polyclonal or engineered to direct specificity to the therapeutic antigen. Recent clinical trials have advanced adoptive immunotherapy with Tregs for the treatment of autoimmune disease and in patients receiving cell transplants. Here, we highlight the potential benefit of combining gene therapy with Treg adoptive transfer to achieve a sustained transgene expression. Furthermore, techniques to engineer antigen-specific Treg cell populations, either through reprogramming conventional CD4+ T cells or transferring T cell receptors with known specificity into polyclonal Tregs, are promising in preclinical studies. Thus, based upon these observations and the successful use of chimeric (IgG-based antigen receptors (CARs in antigen-specific effector T cells, different types of CAR-Tregs could be added to the repertoire of inhibitory modalities to suppress immune responses to therapeutic cargos of gene therapy vectors. The diverse approaches to harness the ability of Tregs to suppress unwanted immune responses to gene therapy and their perspectives are reviewed in this article.

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

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

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

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

    Science.gov (United States)

    Sîrbu, Alina; Crane, Martin; Ruskin, Heather J

    2015-05-14

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

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

    CERN Document Server

    Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

    2015-01-01

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

  17. Algebraic model checking for Boolean gene regulatory networks.

    Science.gov (United States)

    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.

  18. Memory functions reveal structural properties of gene regulatory networks

    Science.gov (United States)

    Perez-Carrasco, Ruben

    2018-01-01

    Gene regulatory networks (GRNs) control cellular function and decision making during tissue development and homeostasis. Mathematical tools based on dynamical systems theory are often used to model these networks, but the size and complexity of these models mean that their behaviour is not always intuitive and the underlying mechanisms can be difficult to decipher. For this reason, methods that simplify and aid exploration of complex networks are necessary. To this end we develop a broadly applicable form of the Zwanzig-Mori projection. By first converting a thermodynamic state ensemble model of gene regulation into mass action reactions we derive a general method that produces a set of time evolution equations for a subset of components of a network. The influence of the rest of the network, the bulk, is captured by memory functions that describe how the subnetwork reacts to its own past state via components in the bulk. These memory functions provide probes of near-steady state dynamics, revealing information not easily accessible otherwise. We illustrate the method on a simple cross-repressive transcriptional motif to show that memory functions not only simplify the analysis of the subnetwork but also have a natural interpretation. We then apply the approach to a GRN from the vertebrate neural tube, a well characterised developmental transcriptional network composed of four interacting transcription factors. The memory functions reveal the function of specific links within the neural tube network and identify features of the regulatory structure that specifically increase the robustness of the network to initial conditions. Taken together, the study provides evidence that Zwanzig-Mori projections offer powerful and effective tools for simplifying and exploring the behaviour of GRNs. PMID:29470492

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

    Directory of Open Access Journals (Sweden)

    David A Garfield

    2013-10-01

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

  20. Uncovering packaging features of co-regulated modules based on human protein interaction and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    He Weiming

    2010-07-01

    Full Text Available Abstract Background Network co-regulated modules are believed to have the functionality of packaging multiple biological entities, and can thus be assumed to coordinate many biological functions in their network neighbouring regions. Results Here, we weighted edges of a human protein interaction network and a transcriptional regulatory network to construct an integrated network, and introduce a probabilistic model and a bipartite graph framework to exploit human co-regulated modules and uncover their specific features in packaging different biological entities (genes, protein complexes or metabolic pathways. Finally, we identified 96 human co-regulated modules based on this method, and evaluate its effectiveness by comparing it with four other methods. Conclusions Dysfunctions in co-regulated interactions often occur in the development of cancer. Therefore, we focussed on an example co-regulated module and found that it could integrate a number of cancer-related genes. This was extended to causal dysfunctions of some complexes maintained by several physically interacting proteins, thus coordinating several metabolic pathways that directly underlie cancer.

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

    Directory of Open Access Journals (Sweden)

    Guo Zheng

    2006-01-01

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

  2. Finding gene regulatory network candidates using the gene expression knowledge base.

    Science.gov (United States)

    Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

    2014-12-10

    Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

  3. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    Science.gov (United States)

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

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

    Science.gov (United States)

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

    2014-03-26

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

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

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2010-03-01

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

  6. Inference of cancer-specific gene regulatory networks using soft computing rules.

    Science.gov (United States)

    Wang, Xiaosheng; Gotoh, Osamu

    2010-03-24

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

  7. Conserved-peptide upstream open reading frames (CPuORFs are associated with regulatory genes in angiosperms

    Directory of Open Access Journals (Sweden)

    Richard A Jorgensen

    2012-08-01

    Full Text Available Upstream open reading frames (uORFs are common in eukaryotic transcripts, but those that encode conserved peptides (CPuORFs occur in less than 1% of transcripts. The peptides encoded by three plant CPuORF families are known to control translation of the downstream ORF in response to a small signal molecule (sucrose, polyamines and phosphocholine. In flowering plants, transcription factors are statistically over-represented among genes that possess CPuORFs, and in general it appeared that many CPuORF genes also had other regulatory functions, though the significance of this suggestion was uncertain (Hayden and Jorgensen, 2007. Five years later the literature provides much more information on the functions of many CPuORF genes. Here we reassess the functions of 27 known CPuORF gene families and find that 22 of these families play a variety of different regulatory roles, from transcriptional control to protein turnover, and from small signal molecules to signal transduction kinases. Clearly then, there is indeed a strong association of CPuORFs with regulatory genes. In addition, 16 of these families play key roles in a variety of different biological processes. Most strikingly, the core sucrose response network includes three different CPuORFs, creating the potential for sophisticated balancing of the network in response to three different molecular inputs. We propose that the function of most CPuORFs is to modulate translation of a downstream major ORF (mORF in response to a signal molecule recognized by the conserved peptide and that because the mORFs of CPuORF genes generally encode regulatory proteins, many of them centrally important in the biology of plants, CPuORFs play key roles in balancing such regulatory networks.

  8. Gene regulatory and signaling networks exhibit distinct topological distributions of motifs

    Science.gov (United States)

    Ferreira, Gustavo Rodrigues; Nakaya, Helder Imoto; Costa, Luciano da Fontoura

    2018-04-01

    The biological processes of cellular decision making and differentiation involve a plethora of signaling pathways and gene regulatory circuits. These networks in turn exhibit a multitude of motifs playing crucial parts in regulating network activity. Here we compare the topological placement of motifs in gene regulatory and signaling networks and observe that it suggests different evolutionary strategies in motif distribution for distinct cellular subnetworks.

  9. A discrete transition zone organizes the topological and regulatory autonomy of the adjacent tfap2c and bmp7 genes.

    Directory of Open Access Journals (Sweden)

    Taro Tsujimura

    2015-01-01

    Full Text Available Despite the well-documented role of remote enhancers in controlling developmental gene expression, the mechanisms that allocate enhancers to genes are poorly characterized. Here, we investigate the cis-regulatory organization of the locus containing the Tfap2c and Bmp7 genes in vivo, using a series of engineered chromosomal rearrangements. While these genes lie adjacent to one another, we demonstrate that they are independently regulated by distinct sets of enhancers, which in turn define non-overlapping regulatory domains. Chromosome conformation capture experiments reveal a corresponding partition of the locus in two distinct structural entities, demarcated by a discrete transition zone. The impact of engineered chromosomal rearrangements on the topology of the locus and the resultant gene expression changes indicate that this transition zone functionally organizes the structural partition of the locus, thereby defining enhancer-target gene allocation. This partition is, however, not absolute: we show that it allows competing interactions across it that may be non-productive for the competing gene, but modulate expression of the competed one. Altogether, these data highlight the prime role of the topological organization of the genome in long-distance regulation of gene expression.

  10. Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

    Science.gov (United States)

    Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

    2015-03-07

    -CM transitions. We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

  11. Differentially expressed regulatory genes in honey bee caste development

    Science.gov (United States)

    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.

  12. Nitrogen modulation of legume root architecture signaling pathways involves phytohormones and small regulatory molecules.

    Science.gov (United States)

    Mohd-Radzman, Nadiatul A; Djordjevic, Michael A; Imin, Nijat

    2013-10-01

    Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules.

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

    Science.gov (United States)

    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. PMID:25200088

  14. Identification and Functional Analysis of Gene Regulatory Sequences Interacting with Colorectal Tumor Suppressors

    DEFF Research Database (Denmark)

    Dahlgaard, Katja; Troelsen, Jesper

    2018-01-01

    Several tumor suppressors possess gene regulatory activity. Here, we describe how promoter and promoter/enhancer reporter assays can be used to characterize a colorectal tumor suppressor proteins’ gene regulatory activity of possible target genes. In the first part, a bioinformatic approach...... of the quick and efficient In-Fusion cloning method, and how to carry out transient transfections of Caco-2 colon cancer cells with the produced luciferase reporter plasmids using polyethyleneimine (PEI). A plan describing how to set up and carry out the luciferase expression assay is presented. The luciferase...... to identify relevant gene regulatory regions of potential target genes is presented. In the second part, it is demonstrated how to prepare and carry out the functional assay. We explain how to clone the bioinformatically identified gene regulatory regions into luciferase reporter plasmids by the use...

  15. Intervention in gene regulatory networks with maximal phenotype alteration.

    Science.gov (United States)

    Yousefi, Mohammadmahdi R; Dougherty, Edward R

    2013-07-15

    A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior. We use a linear programming approach to optimally shift the steady-state mass from undesirable to desirable states, i.e. optimization is directly based on the amount of shift and therefore must outperform previously proposed methods. Moreover, the same basic linear programming structure is used for both unconstrained and constrained optimization, where in the latter case, constraints on the optimization limit the amount of mass that may be shifted to 'ambiguous' states, these being states that are not directly undesirable relative to the pathology of interest but which bear some perceived risk. We apply the method to probabilistic Boolean networks, but the theory applies to any Markovian GRN. Supplementary materials, including the simulation results, MATLAB source code and description of suboptimal methods are available at http://gsp.tamu.edu/Publications/supplementary/yousefi13b. edward@ece.tamu.edu Supplementary data are available at Bioinformatics online.

  16. Human Intellectual Disability Genes Form Conserved Functional Modules in Drosophila

    Science.gov (United States)

    Oortveld, Merel A. W.; Keerthikumar, Shivakumar; Oti, Martin; Nijhof, Bonnie; Fernandes, Ana Clara; Kochinke, Korinna; Castells-Nobau, Anna; van Engelen, Eva; Ellenkamp, Thijs; Eshuis, Lilian; Galy, Anne; van Bokhoven, Hans; Habermann, Bianca; Brunner, Han G.; Zweier, Christiane; Verstreken, Patrik; Huynen, Martijn A.; Schenck, Annette

    2013-01-01

    Intellectual Disability (ID) disorders, defined by an IQ below 70, are genetically and phenotypically highly heterogeneous. Identification of common molecular pathways underlying these disorders is crucial for understanding the molecular basis of cognition and for the development of therapeutic intervention strategies. To systematically establish their functional connectivity, we used transgenic RNAi to target 270 ID gene orthologs in the Drosophila eye. Assessment of neuronal function in behavioral and electrophysiological assays and multiparametric morphological analysis identified phenotypes associated with knockdown of 180 ID gene orthologs. Most of these genotype-phenotype associations were novel. For example, we uncovered 16 genes that are required for basal neurotransmission and have not previously been implicated in this process in any system or organism. ID gene orthologs with morphological eye phenotypes, in contrast to genes without phenotypes, are relatively highly expressed in the human nervous system and are enriched for neuronal functions, suggesting that eye phenotyping can distinguish different classes of ID genes. Indeed, grouping genes by Drosophila phenotype uncovered 26 connected functional modules. Novel links between ID genes successfully predicted that MYCN, PIGV and UPF3B regulate synapse development. Drosophila phenotype groups show, in addition to ID, significant phenotypic similarity also in humans, indicating that functional modules are conserved. The combined data indicate that ID disorders, despite their extreme genetic diversity, are caused by disruption of a limited number of highly connected functional modules. PMID:24204314

  17. Causality analysis detects the regulatory role of maternal effect genes in the early Drosophila embryo

    Directory of Open Access Journals (Sweden)

    Zara Ghodsi

    2017-03-01

    Full Text Available In developmental studies, inferring regulatory interactions of segmentation genetic network play a vital role in unveiling the mechanism of pattern formation. As such, there exists an opportune demand for theoretical developments and new mathematical models which can result in a more accurate illustration of this genetic network. Accordingly, this paper seeks to extract the meaningful regulatory role of the maternal effect genes using a variety of causality detection techniques and to explore whether these methods can suggest a new analytical view to the gene regulatory networks. We evaluate the use of three different powerful and widely-used models representing time and frequency domain Granger causality and convergent cross mapping technique with the results being thoroughly evaluated for statistical significance. Our findings show that the regulatory role of maternal effect genes is detectable in different time classes and thereby the method is applicable to infer the possible regulatory interactions present among the other genes of this network.

  18. Overlapping positive and negative regulatory domains of the human β-interferon gene

    International Nuclear Information System (INIS)

    Goodbourn, S.; Maniatis, T.

    1988-01-01

    Virus of poly(I) x poly(C) induction of human β-interferon gene expression requires a 40-base-pair DNA sequence designated the interferon gene regulatory element (IRE). Previous studies have shown that the IRE contains both positive and negative regulatory DNA sequences. To localize these sequences and study their interactions, the authors have examined the effects of a large number of single-base mutations within the IRE on β-interferon gene regulation. They find that the IRE consists of two genetically separable positive regulatory domains and an overlapping negative control sequence. They propose that the β-interferon gene is switched off in uninduced cells by a repressor that blocks the interaction between one of the two positive regulatory sequences and a specific transcription factor. Induction would then lead to inactivation or displacement of the repressor and binding of transcription factors to both positive regulatory domains

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

    Directory of Open Access Journals (Sweden)

    Dasgupta Dipayan

    2005-05-01

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

  20. Defective distal regulatory element at the 5' upstream of rat prolactin gene of steroid-nonresponsive GH-subclone.

    Science.gov (United States)

    Kumar, V; Wong, D T; Pasion, S G; Biswas, D K

    1987-12-08

    The prolactin-nonproducing (PRL-) GH cell strains (rat pituitary tumor cells in culture). GH12C1 and F1BGH12C1, do not respond to steroid hormones estradiol or hydrocortisone (HC). However, the stimulatory effect of estradiol and the inhibitory effect of hydrocortisone on prolactin synthesis can be demonstrated in the prolactin-producing GH cell strain, GH4C1. In this investigation we have examined the 5' end flanking region of rat prolactin (rat PRL) gene of steroid-responsive, GH4C1 cells to identify the positive and negative regulatory elements and to verify the status of these elements in steroid-nonresponsive F1BGH12C1 cells. Results presented in this report demonstrate that the basel level expression of the co-transferred Neo gene (neomycin phosphoribosyl transferase) is modulated by the distal upstream regulatory elements of rat PRL gene in response to steroid hormones. The expression of adjacent Neo gene is inhibited by dexamethasone and is stimulated by estradiol in transfectants carrying distal regulatory elements (SRE) of steroid-responsive cells. These responses are not observed in transfectants with the rat PRL upstream sequences derived from steroid-nonresponsive cells. The basal level expression of the host cell alpha-2 tubulin gene is not affected by dexamethasone. We report here the identification of the distal steroid regulatory element (SRE) located between 3.8 and 7.8 kb upstream of the transcription initiation site of rat PRL gene. Both the positive and the negative effects of steroid hormones can be identified within this upstream sequence. This distal SRE appears to be nonfunctional in steroid-nonresponsive cells. Though the proximal SRE is functional, the defect in the distal SRE makes the GH substrain nonresponsive to steroid hormones. These results suggest that both the proximal and the distal SREs are essential for the mediation of action of steroid hormones in GH cells.

  1. Combinatorial binding leads to diverse regulatory responses: Lmd is a tissue-specific modulator of Mef2 activity.

    Directory of Open Access Journals (Sweden)

    Paulo M F Cunha

    2010-07-01

    Full Text Available Understanding how complex patterns of temporal and spatial expression are regulated is central to deciphering genetic programs that drive development. Gene expression is initiated through the action of transcription factors and their cofactors converging on enhancer elements leading to a defined activity. Specific constellations of combinatorial occupancy are therefore often conceptualized as rigid binding codes that give rise to a common output of spatio-temporal expression. Here, we assessed this assumption using the regulatory input of two essential transcription factors within the Drosophila myogenic network. Mutations in either Myocyte enhancing factor 2 (Mef2 or the zinc-finger transcription factor lame duck (lmd lead to very similar defects in myoblast fusion, yet the underlying molecular mechanism for this shared phenotype is not understood. Using a combination of ChIP-on-chip analysis and expression profiling of loss-of-function mutants, we obtained a global view of the regulatory input of both factors during development. The majority of Lmd-bound enhancers are co-bound by Mef2, representing a subset of Mef2's transcriptional input during these stages of development. Systematic analyses of the regulatory contribution of both factors demonstrate diverse regulatory roles, despite their co-occupancy of shared enhancer elements. These results indicate that Lmd is a tissue-specific modulator of Mef2 activity, acting as both a transcriptional activator and repressor, which has important implications for myogenesis. More generally, this study demonstrates considerable flexibility in the regulatory output of two factors, leading to additive, cooperative, and repressive modes of co-regulation.

  2. Mode of delivery shapes gut colonization pattern and modulates regulatory immunity in mice

    DEFF Research Database (Denmark)

    Hansen, Camilla Hartmann Friis; Andersen, Line Sidsel Fisker; Krych, Lukasz

    2014-01-01

    diabetes. In this study, we demonstrate that both C-section and cross-fostering with a genetically distinct strain influence the gut microbiota composition and immune key markers in mice. Gut microbiota profiling by denaturing gradient gel electrophoresis and 454/FLX-based 16S rRNA gene amplicon sequencing...... electrophoresis profiles was evident in adult mice. However, the adult C-section-born mice had lower proportions of Foxp3(+) regulatory T cells, tolerogenic CD103(+) dendritic cells, and less Il10 gene expression in mesenteric lymph nodes and spleens. This demonstrates long-term systemic effect on the regulatory...... and priming of regulatory immune system in mice, and mode of delivery strongly influences this....

  3. The nomenclature of MHC class I gene regulatory regions - the case of two different downstream regulatory elements

    Czech Academy of Sciences Publication Activity Database

    Hatina, J.; Jansa, Petr; Forejt, Jiří

    2001-01-01

    Roč. 37, 12-13 (2001), s. 799-800 ISSN 0161-5890 Institutional research plan: CEZ:AV0Z5052915 Keywords : MHC I gene regulatory elements Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 1.973, year: 2001

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

    Lifescience Database Archive (English)

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  7. Plasticity and innovation of regulatory mechanisms underlying seed oil content mediated by duplicated genes in the palaeopolyploid soybean.

    Science.gov (United States)

    Zhang, Dajian; Zhao, Meixia; Li, Shuai; Sun, Lianjun; Wang, Weidong; Cai, Chunmei; Dierking, Emily C; Ma, Jianxin

    2017-06-01

    Many plants have undergone whole genome duplication (WGD). However, how regulatory networks underlying a particular trait are reshaped in polyploids has not been experimentally investigated. Here we show that the regulatory pathways modulating seed oil content, which involve WRINKLED1 (WRI1), LEAFY COTYLEDON1 (LEC1), and LEC2 in Arabidopsis, have been modified in the palaeopolyploid soybean. Such modifications include functional reduction of GmWRI1b of the GmWRI1a/GmWRI1b homoeologous pair relevant to WRI1, complementary non-allelic dosage effects of the GmLEC1a/GmLEC1b homoeologous pair relevant to LEC1, pseudogenization of the singleton GmLEC2 relevant to LEC2, and the rise of the LEC2-like function of GmABI3b, contrasting to its homoeolog GmABI3a, which maintains the ABSCISIC ACID INSENSITIVE 3 (ABI3)-like function in modulating seed maturation and dormancy. The function of GmABI3b in modulating seed oil biosynthesis was fulfilled by direct binding to a RY (CATGCA) cis-regulatory element in the GmWRI1a promoter, which was absent in the GmWRI1b promoter, resulting in reduction of the GmWRI1b expression. Nevertheless, the three regulators each exhibited similar intensities of purifying selection to their respective duplicates since these pairs were formed by a WGD event that is proposed to have occurred approximately 13 million years ago (mya), suggesting that the differentiation in spatiotemporal expression between the duplicated genes is more likely to be the outcome of neutral variation in regulatory sequences. This study thus exemplifies the plasticity, dynamics, and novelty of regulatory networks mediated by WGD. © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

  8. Inferring nonlinear gene regulatory networks from gene expression data based on distance correlation.

    Directory of Open Access Journals (Sweden)

    Xiaobo Guo

    Full Text Available Nonlinear dependence is general in regulation mechanism of gene regulatory networks (GRNs. It is vital to properly measure or test nonlinear dependence from real data for reconstructing GRNs and understanding the complex regulatory mechanisms within the cellular system. A recently developed measurement called the distance correlation (DC has been shown powerful and computationally effective in nonlinear dependence for many situations. In this work, we incorporate the DC into inferring GRNs from the gene expression data without any underling distribution assumptions. We propose three DC-based GRNs inference algorithms: CLR-DC, MRNET-DC and REL-DC, and then compare them with the mutual information (MI-based algorithms by analyzing two simulated data: benchmark GRNs from the DREAM challenge and GRNs generated by SynTReN network generator, and an experimentally determined SOS DNA repair network in Escherichia coli. According to both the receiver operator characteristic (ROC curve and the precision-recall (PR curve, our proposed algorithms significantly outperform the MI-based algorithms in GRNs inference.

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

    Science.gov (United States)

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

    2014-12-01

    Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  10. Network Diffusion-Based Prioritization of Autism Risk Genes Identifies Significantly Connected Gene Modules

    Directory of Open Access Journals (Sweden)

    Ettore Mosca

    2017-09-01

    Full Text Available Autism spectrum disorder (ASD is marked by a strong genetic heterogeneity, which is underlined by the low overlap between ASD risk gene lists proposed in different studies. In this context, molecular networks can be used to analyze the results of several genome-wide studies in order to underline those network regions harboring genetic variations associated with ASD, the so-called “disease modules.” In this work, we used a recent network diffusion-based approach to jointly analyze multiple ASD risk gene lists. We defined genome-scale prioritizations of human genes in relation to ASD genes from multiple studies, found significantly connected gene modules associated with ASD and predicted genes functionally related to ASD risk genes. Most of them play a role in synapsis and neuronal development and function; many are related to syndromes that can be in comorbidity with ASD and the remaining are involved in epigenetics, cell cycle, cell adhesion and cancer.

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

    Science.gov (United States)

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

    2011-01-01

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

  12. Transcriptional modulation of genes encoding nitrate reductase in ...

    African Journals Online (AJOL)

    The free aluminum (Al) content in soil can reach levels that are toxic to plants, and this has frequently limited increased productivity of cultures. Four genes encoding nitrate reductase (NR) were identified, named ZmNR1–4. With the aim of evaluating NR activity and the transcriptional modulation of the ZmNR1, ZmNR2, ...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2005-01-05

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

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

    Science.gov (United States)

    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.

  15. Cis-regulatory somatic mutations and gene-expression alteration in B-cell lymphomas.

    Science.gov (United States)

    Mathelier, Anthony; Lefebvre, Calvin; Zhang, Allen W; Arenillas, David J; Ding, Jiarui; Wasserman, Wyeth W; Shah, Sohrab P

    2015-04-23

    With the rapid increase of whole-genome sequencing of human cancers, an important opportunity to analyze and characterize somatic mutations lying within cis-regulatory regions has emerged. A focus on protein-coding regions to identify nonsense or missense mutations disruptive to protein structure and/or function has led to important insights; however, the impact on gene expression of mutations lying within cis-regulatory regions remains under-explored. We analyzed somatic mutations from 84 matched tumor-normal whole genomes from B-cell lymphomas with accompanying gene expression measurements to elucidate the extent to which these cancers are disrupted by cis-regulatory mutations. We characterize mutations overlapping a high quality set of well-annotated transcription factor binding sites (TFBSs), covering a similar portion of the genome as protein-coding exons. Our results indicate that cis-regulatory mutations overlapping predicted TFBSs are enriched in promoter regions of genes involved in apoptosis or growth/proliferation. By integrating gene expression data with mutation data, our computational approach culminates with identification of cis-regulatory mutations most likely to participate in dysregulation of the gene expression program. The impact can be measured along with protein-coding mutations to highlight key mutations disrupting gene expression and pathways in cancer. Our study yields specific genes with disrupted expression triggered by genomic mutations in either the coding or the regulatory space. It implies that mutated regulatory components of the genome contribute substantially to cancer pathways. Our analyses demonstrate that identifying genomically altered cis-regulatory elements coupled with analysis of gene expression data will augment biological interpretation of mutational landscapes of cancers.

  16. Integration of steady-state and temporal gene expression data for the inference of gene regulatory networks.

    Science.gov (United States)

    Wang, Yi Kan; Hurley, Daniel G; Schnell, Santiago; Print, Cristin G; Crampin, Edmund J

    2013-01-01

    We develop a new regression algorithm, cMIKANA, for inference of gene regulatory networks from combinations of steady-state and time-series gene expression data. Using simulated gene expression datasets to assess the accuracy of reconstructing gene regulatory networks, we show that steady-state and time-series data sets can successfully be combined to identify gene regulatory interactions using the new algorithm. Inferring gene networks from combined data sets was found to be advantageous when using noisy measurements collected with either lower sampling rates or a limited number of experimental replicates. We illustrate our method by applying it to a microarray gene expression dataset from human umbilical vein endothelial cells (HUVECs) which combines time series data from treatment with growth factor TNF and steady state data from siRNA knockdown treatments. Our results suggest that the combination of steady-state and time-series datasets may provide better prediction of RNA-to-RNA interactions, and may also reveal biological features that cannot be identified from dynamic or steady state information alone. Finally, we consider the experimental design of genomics experiments for gene regulatory network inference and show that network inference can be improved by incorporating steady-state measurements with time-series data.

  17. Single nucleotide polymorphism in transcriptional regulatory regions and expression of environmentally responsive genes

    International Nuclear Information System (INIS)

    Wang, Xuting; Tomso, Daniel J.; Liu Xuemei; Bell, Douglas A.

    2005-01-01

    Single nucleotide polymorphisms (SNPs) in the human genome are DNA sequence variations that can alter an individual's response to environmental exposure. SNPs in gene coding regions can lead to changes in the biological properties of the encoded protein. In contrast, SNPs in non-coding gene regulatory regions may affect gene expression levels in an allele-specific manner, and these functional polymorphisms represent an important but relatively unexplored class of genetic variation. The main challenge in analyzing these SNPs is a lack of robust computational and experimental methods. Here, we first outline mechanisms by which genetic variation can impact gene regulation, and review recent findings in this area; then, we describe a methodology for bioinformatic discovery and functional analysis of regulatory SNPs in cis-regulatory regions using the assembled human genome sequence and databases on sequence polymorphism and gene expression. Our method integrates SNP and gene databases and uses a set of computer programs that allow us to: (1) select SNPs, from among the >9 million human SNPs in the NCBI dbSNP database, that are similar to cis-regulatory element (RE) consensus sequences; (2) map the selected dbSNP entries to the human genome assembly in order to identify polymorphic REs near gene start sites; (3) prioritize the candidate polymorphic RE containing genes by searching the existing genotype and gene expression data sets. The applicability of this system has been demonstrated through studies on p53 responsive elements and is being extended to additional pathways and environmentally responsive genes

  18. The phenotypic and molecular assessment of the non-conserved Arabidopsis MICRORNA163/S-ADENOSYL-METHYLTRANSFERASE regulatory module during biotic stress.

    Science.gov (United States)

    Litholdo, Celso Gaspar; Eamens, Andrew Leigh; Waterhouse, Peter Michael

    2018-04-01

    In plants, microRNAs (miRNAs) have evolved in parallel to the protein-coding genes that they target for expression regulation, and miRNA-directed gene expression regulation is central to almost every cellular process. MicroRNA, miR163, is unique to the Arabidopsis genus and is processed into a 24-nucleotide (nt) mature small regulatory RNA (sRNA) from a single precursor transcript transcribed from a single locus, the MIR163 gene. The MIR163 locus is a result of a recent inverted duplication event of one of the five closely related S-ADENOSYL-METHYLTRANSFERASE genes that the mature miR163 sRNA targets for expression regulation. Currently, however, little is known about the role of the miR163/S-ADENOSYL-METHYLTRANSFERASE regulatory module in response to biotic stress. Here, we document the expression domains of MIR163 and the S-ADENOSYL-METHYLTRANSFERASE target genes following fusion of their putative promoter sequences to the β-glucuronidase (GUS) reporter gene and subsequent in planta expression. Further, we report on our phenotypic and molecular assessment of Arabidopsis thaliana plants with altered miR163 accumulation, namely the mir163-1 and mir163-2 insertion knockout mutants and the miR163 overexpression line, the MIR163-OE plant. Finally, we reveal miR163 accumulation and S-ADENOSYL-METHYLTRANSFERASE target gene expression post treatment with the defence elicitors, salicylic acid and jasmonic acid, and following Fusarium oxysporum infection, wounding, and herbivory attack. Together, the work presented here provides a comprehensive new biological insight into the role played by the Arabidopsis genus-specific miR163/S-ADENOSYL-METHYLTRANSFERASE regulatory module in normal A. thaliana development and during the exposure of A. thaliana plants to biotic stress.

  19. Symbiont modulates expression of specific gene categories in Angomonas deanei

    Directory of Open Access Journals (Sweden)

    Luciana Loureiro Penha

    Full Text Available Trypanosomatids are parasites that cause disease in humans, animals, and plants. Most are non-pathogenic and some harbor a symbiotic bacterium. Endosymbiosis is part of the evolutionary process of vital cell functions such as respiration and photosynthesis. Angomonas deanei is an example of a symbiont-containing trypanosomatid. In this paper, we sought to investigate how symbionts influence host cells by characterising and comparing the transcriptomes of the symbiont-containing A. deanei (wild type and the symbiont-free aposymbiotic strains. The comparison revealed that the presence of the symbiont modulates several differentially expressed genes. Empirical analysis of differential gene expression showed that 216 of the 7625 modulated genes were significantly changed. Finally, gene set enrichment analysis revealed that the largest categories of genes that downregulated in the absence of the symbiont were those involved in oxidation-reduction process, ATP hydrolysis coupled proton transport and glycolysis. In contrast, among the upregulated gene categories were those involved in proteolysis, microtubule-based movement, and cellular metabolic process. Our results provide valuable information for dissecting the mechanism of endosymbiosis in A. deanei.

  20. Resistin enhances the expansion of regulatory T cells through modulation of dendritic cells

    Directory of Open Access Journals (Sweden)

    Han Seung

    2010-06-01

    Full Text Available Abstract Background Resistin, a member of adipokine family, is known to be involved in the modulation of immune responses including inflammatory activity. Interestingly, resistin is secreted by adipocytes in mice and rats whereas it is secreted by leukocytes in humans. However, the mechanism behind the effect of resistin on the expansion of regulatory T cells (Tregs remains poorly understood. Therefore, we examined regulatory effect of resistin on the induction and cellular modification of Tregs. Results Both protein and mRNA expression of FoxP3, a representative marker of Tregs, increased in a dose-dependent manner when peripheral blood mononuclear cells were treated with resistin. At the same time, resistin had no direct effect on the induction of FoxP3 in CD4+ T cells, suggesting an indirect role through other cells type(s. Since DCs are an important player in the differentiation of T cells, we focused on the role of DCs in the modulation of Tregs by resistin. Resistin suppressed the expression of interferon regulatory factor (IRF-1 and its target cytokines, IL-6, IL-23p19 and IL-12p40, in DCs. Furthermore, FoxP3 expression is increased in CD4+ T cells when co-cultured with DCs and concomitantly treated with resistin. Conclusion Our results suggest that resistin induces expansion of functional Tregs only when co-cultured with DCs.

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

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    Jennifer Ferguson

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

  2. Computational exploration of cis-regulatory modules in rhythmic expression data using the "Exploration of Distinctive CREs and CRMs" (EDCC) and "CRM Network Generator" (CNG) programs.

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    Bekiaris, Pavlos Stephanos; Tekath, Tobias; Staiger, Dorothee; Danisman, Selahattin

    2018-01-01

    Understanding the effect of cis-regulatory elements (CRE) and clusters of CREs, which are called cis-regulatory modules (CRM), in eukaryotic gene expression is a challenge of computational biology. We developed two programs that allow simple, fast and reliable analysis of candidate CREs and CRMs that may affect specific gene expression and that determine positional features between individual CREs within a CRM. The first program, "Exploration of Distinctive CREs and CRMs" (EDCC), correlates candidate CREs and CRMs with specific gene expression patterns. For pairs of CREs, EDCC also determines positional preferences of the single CREs in relation to each other and to the transcriptional start site. The second program, "CRM Network Generator" (CNG), prioritizes these positional preferences using a neural network and thus allows unbiased rating of the positional preferences that were determined by EDCC. We tested these programs with data from a microarray study of circadian gene expression in Arabidopsis thaliana. Analyzing more than 1.5 million pairwise CRE combinations, we found 22 candidate combinations, of which several contained known clock promoter elements together with elements that had not been identified as relevant to circadian gene expression before. CNG analysis further identified positional preferences of these CRE pairs, hinting at positional information that may be relevant for circadian gene expression. Future wet lab experiments will have to determine which of these combinations confer daytime specific circadian gene expression.

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

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    Baumbach Jan

    2007-11-01

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

  4. In silico analysis of cis-acting regulatory elements in 5' regulatory regions of sucrose transporter gene families in rice (Oryza sativa Japonica) and Arabidopsis thaliana.

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    Ibraheem, Omodele; Botha, Christiaan E J; Bradley, Graeme

    2010-12-01

    The regulation of gene expression involves a multifarious regulatory system. Each gene contains a unique combination of cis-acting regulatory sequence elements in the 5' regulatory region that determines its temporal and spatial expression. Cis-acting regulatory elements are essential transcriptional gene regulatory units; they control many biological processes and stress responses. Thus a full understanding of the transcriptional gene regulation system will depend on successful functional analyses of cis-acting elements. Cis-acting regulatory elements present within the 5' regulatory region of the sucrose transporter gene families in rice (Oryza sativa Japonica cultivar-group) and Arabidopsis thaliana, were identified using a bioinformatics approach. The possible cis-acting regulatory elements were predicted by scanning 1.5kbp of 5' regulatory regions of the sucrose transporter genes translational start sites, using Plant CARE, PLACE and Genomatix Matinspector professional databases. Several cis-acting regulatory elements that are associated with plant development, plant hormonal regulation and stress response were identified, and were present in varying frequencies within the 1.5kbp of 5' regulatory region, among which are; A-box, RY, CAT, Pyrimidine-box, Sucrose-box, ABRE, ARF, ERE, GARE, Me-JA, ARE, DRE, GA-motif, GATA, GT-1, MYC, MYB, W-box, and I-box. This result reveals the probable cis-acting regulatory elements that possibly are involved in the expression and regulation of sucrose transporter gene families in rice and Arabidopsis thaliana during cellular development or environmental stress conditions. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. Nitrogen modulation of legume root architecture signalling pathways involves phytohormones and small regulatory molecules

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    Nadiatul Akmal Mohd-Radzman

    2013-10-01

    Full Text Available Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules.

  6. Tissue-specific expression of aryl hydrocarbon receptor and putative developmental regulatory modules in Baltic salmon yolk-sac fry

    Energy Technology Data Exchange (ETDEWEB)

    Vuori, Kristiina A. [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland)], E-mail: kristiina.vuori@utu.fi; Nordlund, Eija [Department of Information Technology, University of Turku, and Turku Centre for Computer Science (TUCS), FI-20014 Turku (Finland); Kallio, Jenny [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland); Salakoski, Tapio [Department of Information Technology, University of Turku, and Turku Centre for Computer Science (TUCS), FI-20014 Turku (Finland); Nikinmaa, Mikko [Centre of Excellence in Evolutionary Genetics and Physiology, Department of Biology, University of Turku, FI-20014 Turku (Finland)

    2008-04-08

    The aryl hydrocarbon receptor (AhR) is an ancient protein that is conserved in vertebrates and invertebrates, indicating its important function throughout evolution. AhR has been studied largely because of its role in toxicology-gene expression via AhR is induced by many aromatic hydrocarbons in mammals. Recently, however, it has become clear that AhR is involved in various aspects of development such as cell proliferation and differentiation, and cell motility and migration. The mechanisms by which AhR regulates these various functions remain poorly understood. Across-species comparative studies of AhR in invertebrates, non-mammalian vertebrates and mammals may help to reveal the multiple functions of AhR. Here, we have studied AhR during larval development of Baltic salmon (Salmon salar). Our results indicate that AhR protein is expressed in nervous system, liver and muscle tissues. We also present putative regulatory modules and module-matching genes, produced by chromatin immunoprecipitation (ChIP) cloning and in silico analysis, which may be associated with evolutionarily conserved functions of AhR during development. For example, the module NFKB-AHRR-CREB found from salmon ChIP sequences is present in human ULK3 (regulating formation of granule cell axons in mouse and axon outgrowth in Caernohabditis elegans) and SRGAP1 (GTPase-activating protein involved in the Slit/Robo pathway) promoters. We suggest that AhR may have an evolutionarily conserved role in neuronal development and nerve cell targeting, and in Wnt signaling pathway.

  7. Tissue-specific expression of aryl hydrocarbon receptor and putative developmental regulatory modules in Baltic salmon yolk-sac fry

    International Nuclear Information System (INIS)

    Vuori, Kristiina A.; Nordlund, Eija; Kallio, Jenny; Salakoski, Tapio; Nikinmaa, Mikko

    2008-01-01

    The aryl hydrocarbon receptor (AhR) is an ancient protein that is conserved in vertebrates and invertebrates, indicating its important function throughout evolution. AhR has been studied largely because of its role in toxicology-gene expression via AhR is induced by many aromatic hydrocarbons in mammals. Recently, however, it has become clear that AhR is involved in various aspects of development such as cell proliferation and differentiation, and cell motility and migration. The mechanisms by which AhR regulates these various functions remain poorly understood. Across-species comparative studies of AhR in invertebrates, non-mammalian vertebrates and mammals may help to reveal the multiple functions of AhR. Here, we have studied AhR during larval development of Baltic salmon (Salmon salar). Our results indicate that AhR protein is expressed in nervous system, liver and muscle tissues. We also present putative regulatory modules and module-matching genes, produced by chromatin immunoprecipitation (ChIP) cloning and in silico analysis, which may be associated with evolutionarily conserved functions of AhR during development. For example, the module NFKB-AHRR-CREB found from salmon ChIP sequences is present in human ULK3 (regulating formation of granule cell axons in mouse and axon outgrowth in Caernohabditis elegans) and SRGAP1 (GTPase-activating protein involved in the Slit/Robo pathway) promoters. We suggest that AhR may have an evolutionarily conserved role in neuronal development and nerve cell targeting, and in Wnt signaling pathway

  8. Gene expression profiles of immune-regulatory genes in whole blood of cattle with a subclinical infection of Mycobacterium avium subsp. paratuberculosis.

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    Hyun-Eui Park

    Full Text Available Johne's disease is a chronic wasting disease of ruminants caused by Mycobacterium avium subsp. paratuberculosis (MAP, resulting in inflammation of intestines and persistent diarrhea. The initial host response against MAP infections is mainly regulated by the Th1 response, which is characterized by the production of IFN-γ. With the progression of disease, MAP can survive in the host through the evasion of the host's immune response by manipulating the host immune response. However, the host response during subclinical phases has not been fully understood. Immune regulatory genes, including Th17-derived cytokines, interferon regulatory factors, and calcium signaling-associated genes, are hypothesized to play an important role during subclinical phases of Johne's disease. Therefore, the present study was conducted to analyze the expression profiles of immune regulatory genes during MAP infection in whole blood. Different expression patterns of genes were identified depending on the infection stages. Downregulation of IL-17A, IL-17F, IL-22, IL-26, HMGB1, and IRF4 and upregulation of PIP5K1C indicate suppression of the Th1 response due to MAP infection and loss of granuloma integrity. In addition, increased expression of IRF5 and IRF7 suggest activation of IFN-α/β signaling during subclinical stages, which induced indoleamine 2,3-dioxygenase mediated depletion of tryptophan metabolism. Increased expression of CORO1A indicate modulation of calcium signaling, which enhanced the survival of MAP. Taken together, distinct host gene expression induced by MAP infection indicates enhanced survival of MAP during subclinical stages.

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

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    Bor-Sen Chen

    2010-05-01

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

  10. Modulation of DNA binding by gene-specific transcription factors.

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    Schleif, Robert F

    2013-10-01

    The transcription of many genes, particularly in prokaryotes, is controlled by transcription factors whose activity can be modulated by controlling their DNA binding affinity. Understanding the molecular mechanisms by which DNA binding affinity is regulated is important, but because forming definitive conclusions usually requires detailed structural information in combination with data from extensive biophysical, biochemical, and sometimes genetic experiments, little is truly understood about this topic. This review describes the biological requirements placed upon DNA binding transcription factors and their consequent properties, particularly the ways that DNA binding affinity can be modulated and methods for its study. What is known and not known about the mechanisms modulating the DNA binding affinity of a number of prokaryotic transcription factors, including CAP and lac repressor, is provided.

  11. H-ferritin-regulated microRNAs modulate gene expression in K562 cells.

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    Flavia Biamonte

    Full Text Available In a previous study, we showed that the silencing of the heavy subunit (FHC offerritin, the central iron storage molecule in the cell, is accompanied by a modification in global gene expression. In this work, we explored whether different FHC amounts might modulate miRNA expression levels in K562 cells and studied the impact of miRNAs in gene expression profile modifications. To this aim, we performed a miRNA-mRNA integrative analysis in K562 silenced for FHC (K562shFHC comparing it with K562 transduced with scrambled RNA (K562shRNA. Four miRNAs, namely hsa-let-7g, hsa-let-7f, hsa-let-7i and hsa-miR-125b, were significantly up-regulated in silenced cells. The remarkable down-regulation of these miRNAs, following FHC expression rescue, supports a specific relation between FHC silencing and miRNA-modulation. The integration of target predictions with miRNA and gene expression profiles led to the identification of a regulatory network which includes the miRNAs up-regulated by FHC silencing, as well as91 down-regulated putative target genes. These genes were further classified in 9 networks; the highest scoring network, "Cell Death and Survival, Hematological System Development and Function, Hematopoiesis", is composed by 18 focus molecules including RAF1 and ERK1/2. We confirmed that, following FHC silencing, ERK1/2 phosphorylation is severely impaired and that RAF1 mRNA is significantly down-regulated. Taken all together, our data indicate that, in our experimental model, FHC silencing may affect RAF1/pERK1/2 levels through the modulation of a specific set of miRNAs and add new insights in to the relationship among iron homeostasis and miRNAs.

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

    Science.gov (United States)

    Huang, Xin; Li, Hao-ming

    2009-08-05

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

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

    Science.gov (United States)

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

    2011-05-01

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

  14. A guide to approaching regulatory considerations for lentiviral-mediated gene therapies.

    Science.gov (United States)

    White, Michael; Whittaker, Roger; Stoll, Elizabeth Ann

    2017-06-12

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

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

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    Xiaodong Cai

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

  16. Direct activation of a notochord cis-regulatory module by Brachyury and FoxA in the ascidian Ciona intestinalis.

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    Passamaneck, Yale J; Katikala, Lavanya; Perrone, Lorena; Dunn, Matthew P; Oda-Ishii, Izumi; Di Gregorio, Anna

    2009-11-01

    The notochord is a defining feature of the chordate body plan. Experiments in ascidian, frog and mouse embryos have shown that co-expression of Brachyury and FoxA class transcription factors is required for notochord development. However, studies on the cis-regulatory sequences mediating the synergistic effects of these transcription factors are complicated by the limited knowledge of notochord genes and cis-regulatory modules (CRMs) that are directly targeted by both. We have identified an easily testable model for such investigations in a 155-bp notochord-specific CRM from the ascidian Ciona intestinalis. This CRM contains functional binding sites for both Ciona Brachyury (Ci-Bra) and FoxA (Ci-FoxA-a). By combining point mutation analysis and misexpression experiments, we demonstrate that binding of both transcription factors to this CRM is necessary and sufficient to activate transcription. To gain insights into the cis-regulatory criteria controlling its activity, we investigated the organization of the transcription factor binding sites within the 155-bp CRM. The 155-bp sequence contains two Ci-Bra binding sites with identical core sequences but opposite orientations, only one of which is required for enhancer activity. Changes in both orientation and spacing of these sites substantially affect the activity of the CRM, as clusters of identical sites found in the Ciona genome with different arrangements are unable to activate transcription in notochord cells. This work presents the first evidence of a synergistic interaction between Brachyury and FoxA in the activation of an individual notochord CRM, and highlights the importance of transcription factor binding site arrangement for its function.

  17. The antiphasic regulatory module comprising CDF5 and its antisense RNA FLORE links the circadian clock to photoperiodic flowering.

    Science.gov (United States)

    Henriques, Rossana; Wang, Huan; Liu, Jun; Boix, Marc; Huang, Li-Fang; Chua, Nam-Hai

    2017-11-01

    Circadian rhythms of gene expression are generated by the combinatorial action of transcriptional and translational feedback loops as well as chromatin remodelling events. Recently, long noncoding RNAs (lncRNAs) that are natural antisense transcripts (NATs) to transcripts encoding central oscillator components were proposed as modulators of core clock function in mammals (Per) and fungi (frq/qrf). Although oscillating lncRNAs exist in plants, their functional characterization is at an initial stage. By screening an Arabidopsis thaliana lncRNA custom-made array we identified CDF5 LONG NONCODING RNA (FLORE), a circadian-regulated lncRNA that is a NAT of CDF5. Quantitative real-time RT-PCR confirmed the circadian regulation of FLORE, whereas GUS-staining and flowering time evaluation were used to determine its biological function. FLORE and CDF5 antiphasic expression reflects mutual inhibition in a similar way to frq/qrf. Moreover, whereas the CDF5 protein delays flowering by directly repressing FT transcription, FLORE promotes it by repressing several CDFs (CDF1, CDF3, CDF5) and increasing FT transcript levels, indicating both cis and trans function. We propose that the CDF5/FLORE NAT pair constitutes an additional circadian regulatory module with conserved (mutual inhibition) and unique (function in trans) features, able to fine-tune its own circadian oscillation, and consequently, adjust the onset of flowering to favourable environmental conditions. © 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.

  18. A Yin-Yang 1/miR-30a regulatory circuit modulates autophagy in pancreatic cancer cells.

    Science.gov (United States)

    Yang, Chuang; Zhang, Jing-Jing; Peng, Yun-Peng; Zhu, Yi; Yin, Ling-Di; Wei, Ji-Shu; Gao, Wen-Tao; Jiang, Kui-Rong; Miao, Yi

    2017-10-19

    Autophagy is a highly regulated biological process that mediates the degradation of intracellular components. It is required for tumor cell metabolism and homeostasis. Yin-Yang 1 (YY1) has been reported to be involved in autophagy in several carcinomas. However, its role in autophagy in pancreatic cancer, one of the deadliest human malignancies, is unknown. Here, we investigated the function of YY1 in pancreatic cancer cells autophagy and its mechanisms of action. The activity of cells undergoing autophagy was assessed using transmission electron microscopy, immunofluorescence, and Western blotting. A luciferase activity assay, real-time quantitative polymerase chain reaction (RT-qPCR), and chromatin immunoprecipitation (ChIP) were also used to identify putative downstream targets of YY1. YY1 was confirmed to regulate autophagy in pancreatic cancer cells. It was found to directly regulate the expression of miR-30a, a known modulator of autophagy-associated genes. Furthermore, overexpression of miR-30a attenuated the pro-autophagic effects of YY1. Cumulatively, our data suggest that miR-30a acts in a feedback loop to modulate the pro-autophagic activities of YY1. Thus, autophagy in pancreatic cancer cells may be regulated, in part, by a tightly coordinated YY1/miR-30a regulatory circuit. These findings provide a potential druggable target for the development of treatments for pancreatic cancer.

  19. Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

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    Shuchi eSmita

    2015-12-01

    Full Text Available MYB transcription factor (TF is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by top down and guide gene approaches. More than 50% of OsMYBs were strongly correlated under fifty experimental conditions with 51 hub genes via top down approach. Further, clusters were identified using Markov Clustering (MCL. To maximize the clustering performance, parameter evaluation of the MCL inflation score (I was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by guide gene approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought

  20. Cis-regulatory timers for developmental gene expression.

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    Lionel Christiaen

    2013-10-01

    Full Text Available 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.

  1. Safety assessment of immunomodulatory biologics: the promise and challenges of regulatory T-cell modulation.

    Science.gov (United States)

    Ponce, Rafael A

    2011-01-01

    Regulatory T-cell (T(reg)) modulation is developing as an important therapeutic opportunity for the treatment of a number of important diseases, including cancer, autoimmunity, infection, and organ transplant rejection. However, as demonstrated with IL-2 and TGN-1412, our understanding of the complex immunological interactions that occur with T(reg) modulation in both non-clinical models and in patients remains limited and appears highly contextual. This lack of understanding will challenge our ability to identify the patient population who might derive the highest benefit from T(reg) modulation and creates special challenges as we transition these therapeutics from non-clinical models into humans. Thus, in vivo testing in the most representative animal model systems, with careful progress in the clinic, will remain critical in developing therapeutics targeting T(reg) and understanding their clinical utility. Moreover, toxicology models can inform some of the potential liabilities associated with T(reg) modulation, but not all, suggesting a continued need to explore and validate predictive models.

  2. Sterol regulatory element-binding proteins are regulators of the rat thyroid peroxidase gene in thyroid cells.

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    Christine Rauer

    Full Text Available Sterol regulatory element-binding proteins (SREBPs-1c and -2, which were initially discovered as master transcriptional regulators of lipid biosynthesis and uptake, were recently identified as novel transcriptional regulators of the sodium-iodide symporter gene in the thyroid, which is essential for thyroid hormone synthesis. Based on this observation that SREBPs play a role for thyroid hormone synthesis, we hypothesized that another gene involved in thyroid hormone synthesis, the thyroid peroxidase (TPO gene, is also a target of SREBP-1c and -2. Thyroid epithelial cells treated with 25-hydroxycholesterol, which is known to inhibit SREBP activation, had about 50% decreased mRNA levels of TPO. Similarly, the mRNA level of TPO was reduced by about 50% in response to siRNA mediated knockdown of both, SREBP-1 and SREBP-2. Reporter gene assays revealed that overexpression of active SREBP-1c and -2 causes a strong transcriptional activation of the rat TPO gene, which was localized to an approximately 80 bp region in the intron 1 of the rat TPO gene. In vitro- and in vivo-binding of both, SREBP-1c and SREBP-2, to this region in the rat TPO gene could be demonstrated using gel-shift assays and chromatin immunoprecipitation. Mutation analysis of the 80 bp region of rat TPO intron 1 revealed two isolated and two overlapping SREBP-binding elements from which one, the overlapping SRE+609/InvSRE+614, was shown to be functional in reporter gene assays. In connection with recent findings that the rat NIS gene is also a SREBP target gene in the thyroid, the present findings suggest that SREBPs may be possible novel targets for pharmacological modulation of thyroid hormone synthesis.

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

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    Frank Emmert-Streib

    2013-02-01

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

  4. Hydrogen-Deuterium Exchange Mass Spectrometry Reveals Calcium Binding Properties and Allosteric Regulation of Downstream Regulatory Element Antagonist Modulator (DREAM).

    Science.gov (United States)

    Zhang, Jun; Li, Jing; Craig, Theodore A; Kumar, Rajiv; Gross, Michael L

    2017-07-18

    Downstream regulatory element antagonist modulator (DREAM) is an EF-hand Ca 2+ -binding protein that also binds to a specific DNA sequence, downstream regulatory elements (DRE), and thereby regulates transcription in a calcium-dependent fashion. DREAM binds to DRE in the absence of Ca 2+ but detaches from DRE under Ca 2+ stimulation, allowing gene expression. The Ca 2+ binding properties of DREAM and the consequences of the binding on protein structure are key to understanding the function of DREAM. Here we describe the application of hydrogen-deuterium exchange mass spectrometry (HDX-MS) and site-directed mutagenesis to investigate the Ca 2+ binding properties and the subsequent conformational changes of full-length DREAM. We demonstrate that all EF-hands undergo large conformation changes upon calcium binding even though the EF-1 hand is not capable of binding to Ca 2+ . Moreover, EF-2 is a lower-affinity site compared to EF-3 and -4 hands. Comparison of HDX profiles between wild-type DREAM and two EF-1 mutated constructs illustrates that the conformational changes in the EF-1 hand are induced by long-range structural interactions. HDX analyses also reveal a conformational change in an N-terminal leucine-charged residue-rich domain (LCD) remote from Ca 2+ -binding EF-hands. This LCD domain is responsible for the direct interaction between DREAM and cAMP response element-binding protein (CREB) and regulates the recruitment of the co-activator, CREB-binding protein. These long-range interactions strongly suggest how conformational changes transmit the Ca 2+ signal to CREB-mediated gene transcription.

  5. Gene regulatory network inference by point-based Gaussian approximation filters incorporating the prior information.

    Science.gov (United States)

    Jia, Bin; Wang, Xiaodong

    2013-12-17

    : The extended Kalman filter (EKF) has been applied to inferring gene regulatory networks. However, it is well known that the EKF becomes less accurate when the system exhibits high nonlinearity. In addition, certain prior information about the gene regulatory network exists in practice, and no systematic approach has been developed to incorporate such prior information into the Kalman-type filter for inferring the structure of the gene regulatory network. In this paper, an inference framework based on point-based Gaussian approximation filters that can exploit the prior information is developed to solve the gene regulatory network inference problem. Different point-based Gaussian approximation filters, including the unscented Kalman filter (UKF), the third-degree cubature Kalman filter (CKF3), and the fifth-degree cubature Kalman filter (CKF5) are employed. Several types of network prior information, including the existing network structure information, sparsity assumption, and the range constraint of parameters, are considered, and the corresponding filters incorporating the prior information are developed. Experiments on a synthetic network of eight genes and the yeast protein synthesis network of five genes are carried out to demonstrate the performance of the proposed framework. The results show that the proposed methods provide more accurate inference results than existing methods, such as the EKF and the traditional UKF.

  6. Regulatory Considerations for Gene Therapy Products in the US, EU, and Japan.

    Science.gov (United States)

    Halioua-Haubold, Celine-Lea; Peyer, James G; Smith, James A; Arshad, Zeeshaan; Scholz, Matthew; Brindley, David A; MacLaren, Robert E

    2017-12-01

    Developers of gene therapy products (GTPs) must adhere to additional regulation beyond that of traditional small-molecule therapeutics, due to the unique mechanism-of-action of GTPs and the subsequent novel risks arisen. We have provided herein a summary of the regulatory structure under which GTPs fall in the United States, the European Union, and Japan, and a comprehensive overview of the regulatory guidance applicable to the developer of GTP. Understanding the regulatory requirements for seeking GTP market approval in these major jurisdictions is crucial for an effective and expedient path to market. The novel challenges facing GTP developers is highlighted by a case study of alipogene tiparvovec (Glybera).

  7. A flood-based information flow analysis and network minimization method for gene regulatory networks.

    Science.gov (United States)

    Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

    2013-04-24

    Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.

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

    Science.gov (United States)

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

    2006-07-01

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

  9. Identifying noncoding risk variants using disease-relevant gene regulatory networks.

    Science.gov (United States)

    Gao, Long; Uzun, Yasin; Gao, Peng; He, Bing; Ma, Xiaoke; Wang, Jiahui; Han, Shizhong; Tan, Kai

    2018-02-16

    Identifying noncoding risk variants remains a challenging task. Because noncoding variants exert their effects in the context of a gene regulatory network (GRN), we hypothesize that explicit use of disease-relevant GRNs can significantly improve the inference accuracy of noncoding risk variants. We describe Annotation of Regulatory Variants using Integrated Networks (ARVIN), a general computational framework for predicting causal noncoding variants. It employs a set of novel regulatory network-based features, combined with sequence-based features to infer noncoding risk variants. Using known causal variants in gene promoters and enhancers in a number of diseases, we show ARVIN outperforms state-of-the-art methods that use sequence-based features alone. Additional experimental validation using reporter assay further demonstrates the accuracy of ARVIN. Application of ARVIN to seven autoimmune diseases provides a holistic view of the gene subnetwork perturbed by the combinatorial action of the entire set of risk noncoding mutations.

  10. Postinduction represssion of the β-interferon gene is mediated through two positive regulatory domains

    International Nuclear Information System (INIS)

    Whittemore, L.A.; Maniatis, T.

    1990-01-01

    Virus induction of the human β-interferon (β-IFN) gene results in an increase in the rate of β-IFN mRNA synthesis, followed by a rapid postinduction decrease. In this paper, the authors show that two β-IFN promoter elements, positive regulatory domains I and II (PRDI and PRDII), which are required for virus induction of the β-IFN gene are also required for the postinduction turnoff. Although protein synthesis is not necessary for activation, it is necessary for repression of these promoter elements. Examination of nuclear extracts from cells infected with virus reveals the presence of virus-inducible, cycloheximide-sensitive, DNA-binding activities that interact specifically with PRDI or PRDII. They propose that the postinduction repression of β-IFN gene transcription involves virus inducible repressors that either bind directly to the positive regulatory elements of the β-IFN promoter or inactivate the positive regulatory factors bound to PRDI and PRDII

  11. Nanoparticle curcumin ameliorates experimental colitis via modulation of gut microbiota and induction of regulatory T cells.

    Directory of Open Access Journals (Sweden)

    Masashi Ohno

    Full Text Available Curcumin is a hydrophobic polyphenol derived from turmeric, a traditional Indian spice. Curcumin exhibits various biological functions, but its clinical application is limited due to its poor absorbability after oral administration. A newly developed nanoparticle curcumin shows improved absorbability in vivo. In this study, we examined the effects of nanoparticle curcumin (named Theracurmin on experimental colitis in mice.BALB/c mice were fed with 3% dextran sulfate sodium (DSS in water. Mucosal cytokine expression and lymphocyte subpopulation were analyzed by real-time PCR and flow cytometry, respectively. The profile of the gut microbiota was analyzed by real-time PCR.Treatment with nanoparticle curcumin significantly attenuated body weight loss, disease activity index, histological colitis score and significantly improved mucosal permeability. Immunoblot analysis showed that NF-κB activation in colonic epithelial cells was significantly suppressed by treatment with nanoparticle curcumin. Mucosal mRNA expression of inflammatory mediators was significantly suppressed by treatment with nanoparticle curcumin. Treatment with nanoparticle curcumin increased the abundance of butyrate-producing bacteria and fecal butyrate level. This was accompanied by increased expansion of CD4+ Foxp3+ regulatory T cells and CD103+ CD8α- regulatory dendritic cells in the colonic mucosa.Treatment with nanoparticle curcumin suppressed the development of DSS-induced colitis potentially via modulation of gut microbial structure. These responses were associated with induction of mucosal immune cells with regulatory properties. Nanoparticle curcumin is one of the promising candidates as a therapeutic option for the treatment of IBD.

  12. Using reporter gene assays to identify cis regulatory differences between humans and chimpanzees.

    Science.gov (United States)

    Chabot, Adrien; Shrit, Ralla A; Blekhman, Ran; Gilad, Yoav

    2007-08-01

    Most phenotypic differences between human and chimpanzee are likely to result from differences in gene regulation, rather than changes to protein-coding regions. To date, however, only a handful of human-chimpanzee nucleotide differences leading to changes in gene regulation have been identified. To hone in on differences in regulatory elements between human and chimpanzee, we focused on 10 genes that were previously found to be differentially expressed between the two species. We then designed reporter gene assays for the putative human and chimpanzee promoters of the 10 genes. Of seven promoters that we found to be active in human liver cell lines, human and chimpanzee promoters had significantly different activity in four cases, three of which recapitulated the gene expression difference seen in the microarray experiment. For these three genes, we were therefore able to demonstrate that a change in cis influences expression differences between humans and chimpanzees. Moreover, using site-directed mutagenesis on one construct, the promoter for the DDA3 gene, we were able to identify three nucleotides that together lead to a cis regulatory difference between the species. High-throughput application of this approach can provide a map of regulatory element differences between humans and our close evolutionary relatives.

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

    Science.gov (United States)

    Luo, Yonglun; Blechingberg, Jenny; Fernandes, Ana Miguel; Li, Shengting; Fryland, Tue; Børglum, Anders D; Bolund, Lars; Nielsen, Anders Lade

    2015-11-14

    FUS (TLS) and EWS (EWSR1) belong to the FET-protein family of RNA and DNA binding proteins. FUS and EWS are structurally and functionally related and participate in transcriptional regulation and RNA processing. FUS and EWS are identified in translocation generated cancer fusion proteins and involved in the human neurological diseases amyotrophic lateral sclerosis and fronto-temporal lobar degeneration. To determine the gene regulatory functions of FUS and EWS at the level of chromatin, we have performed chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq). Our results show that FUS and EWS bind to a subset of actively transcribed genes, that binding often is downstream the poly(A)-signal, and that binding overlaps with RNA polymerase II. Functional examinations of selected target genes identified that FUS and EWS can regulate gene expression at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes involved in pathways at the RNA regulatory level with potential to mediate normal and disease-associated functions of the FUS and EWS proteins.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-06-01

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

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

    Science.gov (United States)

    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. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  16. Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies

    Science.gov (United States)

    2014-01-01

    Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods. PMID:24708878

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

    DEFF Research Database (Denmark)

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

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Takeshi Hase

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

  19. Safety assessment considerations for food and feed derived from plants with genetic modifications that modulate endogenous gene expression and pathways.

    Science.gov (United States)

    Kier, Larry D; Petrick, Jay S

    2008-08-01

    The current globally recognized comparative food and feed safety assessment paradigm for biotechnology-derived crops is a robust and comprehensive approach for evaluating the safety of both the inserted gene product and the resulting crop. Incorporating many basic concepts from food safety, toxicology, nutrition, molecular biology, and plant breeding, this approach has been used effectively by scientists and regulatory agencies for 10-15 years. Current and future challenges in agriculture include the need for improved yields, tolerance to biotic and abiotic stresses, and improved nutrition. The next generation of biotechnology-derived crops may utilize regulatory proteins, such as transcription factors that modulate gene expression and/or endogenous plant pathways. In this review, we discuss the applicability of the current safety assessment paradigm to biotechnology-derived crops developed using modifications involving regulatory proteins. The growing literature describing the molecular biology underlying plant domestication and conventional breeding demonstrates the naturally occurring genetic variation found in plants, including significant variation in the classes, expression, and activity of regulatory proteins. Specific examples of plant modifications involving insertion or altered expression of regulatory proteins are discussed as illustrative case studies supporting the conclusion that the current comparative safety assessment process is appropriate for these types of biotechnology-developed crops.

  20. Sarcoptes scabiei mites modulate gene expression in human skin equivalents.

    Directory of Open Access Journals (Sweden)

    Marjorie S Morgan

    Full Text Available The ectoparasitic mite, Sarcoptes scabiei that burrows in the epidermis of mammalian skin has a long co-evolution with its hosts. Phenotypic studies show that the mites have the ability to modulate cytokine secretion and expression of cell adhesion molecules in cells of the skin and other cells of the innate and adaptive immune systems that may assist the mites to survive in the skin. The purpose of this study was to identify genes in keratinocytes and fibroblasts in human skin equivalents (HSEs that changed expression in response to the burrowing of live scabies mites. Overall, of the more than 25,800 genes measured, 189 genes were up-regulated >2-fold in response to scabies mite burrowing while 152 genes were down-regulated to the same degree. HSEs differentially expressed large numbers of genes that were related to host protective responses including those involved in immune response, defense response, cytokine activity, taxis, response to other organisms, and cell adhesion. Genes for the expression of interleukin-1α (IL-1α precursor, IL-1β, granulocyte/macrophage-colony stimulating factor (GM-CSF precursor, and G-CSF precursor were up-regulated 2.8- to 7.4-fold, paralleling cytokine secretion profiles. A large number of genes involved in epithelium development and keratinization were also differentially expressed in response to live scabies mites. Thus, these skin cells are directly responding as expected in an inflammatory response to products of the mites and the disruption of the skin's protective barrier caused by burrowing. This suggests that in vivo the interplay among these skin cells and other cell types, including Langerhans cells, dendritic cells, lymphocytes and endothelial cells, is responsible for depressing the host's protective response allowing these mites to survive in the skin.

  1. Sarcoptes scabiei Mites Modulate Gene Expression in Human Skin Equivalents

    Science.gov (United States)

    Morgan, Marjorie S.; Arlian, Larry G.; Markey, Michael P.

    2013-01-01

    The ectoparasitic mite, Sarcoptes scabiei that burrows in the epidermis of mammalian skin has a long co-evolution with its hosts. Phenotypic studies show that the mites have the ability to modulate cytokine secretion and expression of cell adhesion molecules in cells of the skin and other cells of the innate and adaptive immune systems that may assist the mites to survive in the skin. The purpose of this study was to identify genes in keratinocytes and fibroblasts in human skin equivalents (HSEs) that changed expression in response to the burrowing of live scabies mites. Overall, of the more than 25,800 genes measured, 189 genes were up-regulated >2-fold in response to scabies mite burrowing while 152 genes were down-regulated to the same degree. HSEs differentially expressed large numbers of genes that were related to host protective responses including those involved in immune response, defense response, cytokine activity, taxis, response to other organisms, and cell adhesion. Genes for the expression of interleukin-1α (IL-1α) precursor, IL-1β, granulocyte/macrophage-colony stimulating factor (GM-CSF) precursor, and G-CSF precursor were up-regulated 2.8- to 7.4-fold, paralleling cytokine secretion profiles. A large number of genes involved in epithelium development and keratinization were also differentially expressed in response to live scabies mites. Thus, these skin cells are directly responding as expected in an inflammatory response to products of the mites and the disruption of the skin’s protective barrier caused by burrowing. This suggests that in vivo the interplay among these skin cells and other cell types, including Langerhans cells, dendritic cells, lymphocytes and endothelial cells, is responsible for depressing the host’s protective response allowing these mites to survive in the skin. PMID:23940705

  2. Analysis of regulatory networks constructed based on gene ...

    Indian Academy of Sciences (India)

    2013-12-09

    Dec 9, 2013 ... early diagnosis of complex diseases or cancer without obvious symptoms. [Gong J., Diao B., Yao G. J., ... expression levels of thousands of genes in a specific cell or tissue. Previous ..... base of the brain. It mainly controls the ...

  3. The PAZAR database of gene regulatory information coupled to the ORCA toolkit for the study of regulatory sequences

    Science.gov (United States)

    Portales-Casamar, Elodie; Arenillas, David; Lim, Jonathan; Swanson, Magdalena I.; Jiang, Steven; McCallum, Anthony; Kirov, Stefan; Wasserman, Wyeth W.

    2009-01-01

    The PAZAR database unites independently created and maintained data collections of transcription factor and regulatory sequence annotation. The flexible PAZAR schema permits the representation of diverse information derived from experiments ranging from biochemical protein–DNA binding to cellular reporter gene assays. Data collections can be made available to the public, or restricted to specific system users. The data ‘boutiques’ within the shopping-mall-inspired system facilitate the analysis of genomics data and the creation of predictive models of gene regulation. Since its initial release, PAZAR has grown in terms of data, features and through the addition of an associated package of software tools called the ORCA toolkit (ORCAtk). ORCAtk allows users to rapidly develop analyses based on the information stored in the PAZAR system. PAZAR is available at http://www.pazar.info. ORCAtk can be accessed through convenient buttons located in the PAZAR pages or via our website at http://www.cisreg.ca/ORCAtk. PMID:18971253

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

    DEFF Research Database (Denmark)

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

    2015-01-01

    at different levels. Gene Ontology analyses showed that FUS and EWS target genes preferentially encode proteins involved in regulatory processes at the RNA level. Conclusions The presented results yield new insights into gene interactions of EWS and FUS and have identified a set of FUS and EWS target genes...... involved in pathways at the RNA regulatory level with potential to mediate normal and disease-associated functions of the FUS and EWS proteins.......Background FUS (TLS) and EWS (EWSR1) belong to the FET-protein family of RNA and DNA binding proteins. FUS and EWS are structurally and functionally related and participate in transcriptional regulation and RNA processing. FUS and EWS are identified in translocation generated cancer fusion proteins...

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

    Science.gov (United States)

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

    2017-01-01

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

  6. Co-ordinate regulation of Salmonella typhimurium invasion genes by environmental and regulatory factors is mediated by control of hilA expression.

    Science.gov (United States)

    Bajaj, V; Lucas, R L; Hwang, C; Lee, C A

    1996-11-01

    During infection of their hosts, salmonellae enter intestinal epithelial cells. It has been proposed that when Salmonella typhimurium is present in the intestinal lumen, several environmental and regulatory conditions modulate the expression of invasion factors required for bacterial entry into host cells. We report here that the expression of six different S. typhimurium invasion genes encoded on SPI1 (Salmonella pathogenicity island 1) is co-ordinately regulated by oxygen, osmolarity, pH, PhoPQ, and HilA. HilA is a transcriptional activator of the OmpR/ToxR family that is also encoded on SPI1. We have found that HilA plays a central role in the co-ordinated regulation of invasion genes by environmental and regulatory conditions. HilA can activate the expression of two invasion gene-lacZY fusions on reporter plasmids in Escherichia coll, suggesting that HilA acts directly at invasion-gene promoters in S. typhimurium. We have found that the regulation of invasion genes by oxygen, osmolarity, pH, and PhoPQ is indirect and is mediated by regulation of hilA expression by these environmental and regulatory factors. We hypothesize that the complex and co-ordinate regulation of Invasion genes by HilA is an important feature of salmonella pathogenesis and allows salmonellae to enter intestinal epithelial cells.

  7. IBTK Differently Modulates Gene Expression and RNA Splicing in HeLa and K562 Cells

    Directory of Open Access Journals (Sweden)

    Giuseppe Fiume

    2016-11-01

    Full Text Available The IBTK gene encodes the major protein isoform IBTKα that was recently characterized as substrate receptor of Cul3-dependent E3 ligase, regulating ubiquitination coupled to proteasomal degradation of Pdcd4, an inhibitor of translation. Due to the presence of Ankyrin-BTB-RCC1 domains that mediate several protein-protein interactions, IBTKα could exert expanded regulatory roles, including interaction with transcription regulators. To verify the effects of IBTKα on gene expression, we analyzed HeLa and K562 cell transcriptomes by RNA-Sequencing before and after IBTK knock-down by shRNA transduction. In HeLa cells, 1285 (2.03% of 63,128 mapped transcripts were differentially expressed in IBTK-shRNA-transduced cells, as compared to cells treated with control-shRNA, with 587 upregulated (45.7% and 698 downregulated (54.3% RNAs. In K562 cells, 1959 (3.1% of 63128 mapped RNAs were differentially expressed in IBTK-shRNA-transduced cells, including 1053 upregulated (53.7% and 906 downregulated (46.3%. Only 137 transcripts (0.22% were commonly deregulated by IBTK silencing in both HeLa and K562 cells, indicating that most IBTKα effects on gene expression are cell type-specific. Based on gene ontology classification, the genes responsive to IBTK are involved in different biological processes, including in particular chromatin and nucleosomal organization, gene expression regulation, and cellular traffic and migration. In addition, IBTK RNA interference affected RNA maturation in both cell lines, as shown by the evidence of alternative 3′- and 5′-splicing, mutually exclusive exons, retained introns, and skipped exons. Altogether, these results indicate that IBTK differently modulates gene expression and RNA splicing in HeLa and K562 cells, demonstrating a novel biological role of this protein.

  8. IBTK Differently Modulates Gene Expression and RNA Splicing in HeLa and K562 Cells.

    Science.gov (United States)

    Fiume, Giuseppe; Scialdone, Annarita; Rizzo, Francesca; De Filippo, Maria Rosaria; Laudanna, Carmelo; Albano, Francesco; Golino, Gaetanina; Vecchio, Eleonora; Pontoriero, Marilena; Mimmi, Selena; Ceglia, Simona; Pisano, Antonio; Iaccino, Enrico; Palmieri, Camillo; Paduano, Sergio; Viglietto, Giuseppe; Weisz, Alessandro; Scala, Giuseppe; Quinto, Ileana

    2016-11-07

    The IBTK gene encodes the major protein isoform IBTKα that was recently characterized as substrate receptor of Cul3-dependent E3 ligase, regulating ubiquitination coupled to proteasomal degradation of Pdcd4, an inhibitor of translation. Due to the presence of Ankyrin-BTB-RCC1 domains that mediate several protein-protein interactions, IBTKα could exert expanded regulatory roles, including interaction with transcription regulators. To verify the effects of IBTKα on gene expression, we analyzed HeLa and K562 cell transcriptomes by RNA-Sequencing before and after IBTK knock-down by shRNA transduction. In HeLa cells, 1285 (2.03%) of 63,128 mapped transcripts were differentially expressed in IBTK -shRNA-transduced cells, as compared to cells treated with control-shRNA, with 587 upregulated (45.7%) and 698 downregulated (54.3%) RNAs. In K562 cells, 1959 (3.1%) of 63128 mapped RNAs were differentially expressed in IBTK -shRNA-transduced cells, including 1053 upregulated (53.7%) and 906 downregulated (46.3%). Only 137 transcripts (0.22%) were commonly deregulated by IBTK silencing in both HeLa and K562 cells, indicating that most IBTKα effects on gene expression are cell type-specific. Based on gene ontology classification, the genes responsive to IBTK are involved in different biological processes, including in particular chromatin and nucleosomal organization, gene expression regulation, and cellular traffic and migration. In addition, IBTK RNA interference affected RNA maturation in both cell lines, as shown by the evidence of alternative 3'- and 5'-splicing, mutually exclusive exons, retained introns, and skipped exons. Altogether, these results indicate that IBTK differently modulates gene expression and RNA splicing in HeLa and K562 cells, demonstrating a novel biological role of this protein.

  9. Design of Knowledge Bases for Plant Gene Regulatory Networks.

    Science.gov (United States)

    Mukundi, Eric; Gomez-Cano, Fabio; Ouma, Wilberforce Zachary; Grotewold, Erich

    2017-01-01

    Developing a knowledge base that contains all the information necessary for the researcher studying gene regulation in a particular organism can be accomplished in four stages. This begins with defining the data scope. We describe here the necessary information and resources, and outline the methods for obtaining data. The second stage consists of designing the schema, which involves defining the entire arrangement of the database in a systematic plan. The third stage is the implementation, defined by actualization of the database by using software according to a predefined schema. The final stage is development, where the database is made available to users in a web-accessible system. The result is a knowledgebase that integrates all the information pertaining to gene regulation, and which is easily expandable and transferable.

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

    Science.gov (United States)

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

    2014-12-01

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

  11. Clock gene modulates roles of OXTR and AVPR1b genes in prosociality.

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    Haipeng Ci

    Full Text Available BACKGROUND: The arginine vasopressin receptor (AVPR and oxytocin receptor (OXTR genes have been demonstrated to contribute to prosocial behavior. Recent research has focused on the manner by which these simple receptor genes influence prosociality, particularly with regard to the AVP system, which is modulated by the clock gene. The clock gene is responsible for regulating the human biological clock, affecting sleep, emotion and behavior. The current study examined in detail whether the influences of the OXTR and AVPR1b genes on prosociality are dependent on the clock gene. METHODOLOGY/PRINCIPAL FINDINGS: This study assessed interactions between the clock gene (rs1801260, rs6832769 and the OXTR (rs1042778, rs237887 and AVPR1b (rs28373064 genes in association with individual differences in prosociality in healthy male Chinese subjects (n = 436. The Prosocial Tendencies Measure (PTM-R was used to assess prosociality. Participants carrying both the GG/GA variant of AVPR1b rs28373064 and the AA variant of clock rs6832769 showed the highest scores on the Emotional PTM. Carriers of both the T allele of OXTR rs1042778 and the C allele of clock rs1801260 showed the lowest total PTM scores compared with the other groups. CONCLUSIONS: The observed interaction effects provide converging evidence that the clock gene and OXT/AVP systems are intertwined and contribute to human prosociality.

  12. Clock gene modulates roles of OXTR and AVPR1b genes in prosociality.

    Science.gov (United States)

    Ci, Haipeng; Wu, Nan; Su, Yanjie

    2014-01-01

    The arginine vasopressin receptor (AVPR) and oxytocin receptor (OXTR) genes have been demonstrated to contribute to prosocial behavior. Recent research has focused on the manner by which these simple receptor genes influence prosociality, particularly with regard to the AVP system, which is modulated by the clock gene. The clock gene is responsible for regulating the human biological clock, affecting sleep, emotion and behavior. The current study examined in detail whether the influences of the OXTR and AVPR1b genes on prosociality are dependent on the clock gene. This study assessed interactions between the clock gene (rs1801260, rs6832769) and the OXTR (rs1042778, rs237887) and AVPR1b (rs28373064) genes in association with individual differences in prosociality in healthy male Chinese subjects (n = 436). The Prosocial Tendencies Measure (PTM-R) was used to assess prosociality. Participants carrying both the GG/GA variant of AVPR1b rs28373064 and the AA variant of clock rs6832769 showed the highest scores on the Emotional PTM. Carriers of both the T allele of OXTR rs1042778 and the C allele of clock rs1801260 showed the lowest total PTM scores compared with the other groups. The observed interaction effects provide converging evidence that the clock gene and OXT/AVP systems are intertwined and contribute to human prosociality.

  13. Cooperative adaptive responses in gene regulatory networks with many degrees of freedom.

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    Inoue, Masayo; Kaneko, Kunihiko

    2013-04-01

    Cells generally adapt to environmental changes by first exhibiting an immediate response and then gradually returning to their original state to achieve homeostasis. Although simple network motifs consisting of a few genes have been shown to exhibit such adaptive dynamics, they do not reflect the complexity of real cells, where the expression of a large number of genes activates or represses other genes, permitting adaptive behaviors. Here, we investigated the responses of gene regulatory networks containing many genes that have undergone numerical evolution to achieve high fitness due to the adaptive response of only a single target gene; this single target gene responds to changes in external inputs and later returns to basal levels. Despite setting a single target, most genes showed adaptive responses after evolution. Such adaptive dynamics were not due to common motifs within a few genes; even without such motifs, almost all genes showed adaptation, albeit sometimes partial adaptation, in the sense that expression levels did not always return to original levels. The genes split into two groups: genes in the first group exhibited an initial increase in expression and then returned to basal levels, while genes in the second group exhibited the opposite changes in expression. From this model, genes in the first group received positive input from other genes within the first group, but negative input from genes in the second group, and vice versa. Thus, the adaptation dynamics of genes from both groups were consolidated. This cooperative adaptive behavior was commonly observed if the number of genes involved was larger than the order of ten. These results have implications in the collective responses of gene expression networks in microarray measurements of yeast Saccharomyces cerevisiae and the significance to the biological homeostasis of systems with many components.

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

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    Allan Andrew C

    2008-07-01

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

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

    International Nuclear Information System (INIS)

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

    1989-01-01

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

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

    Science.gov (United States)

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

  17. Predictive minimum description length principle approach to inferring gene regulatory networks.

    Science.gov (United States)

    Chaitankar, Vijender; Zhang, Chaoyang; Ghosh, Preetam; Gong, Ping; Perkins, Edward J; Deng, Youping

    2011-01-01

    Reverse engineering of gene regulatory networks using information theory models has received much attention due to its simplicity, low computational cost, and capability of inferring large networks. One of the major problems with information theory models is to determine the threshold that defines the regulatory relationships between genes. The minimum description length (MDL) principle has been implemented to overcome this problem. The description length of the MDL principle is the sum of model length and data encoding length. A user-specified fine tuning parameter is used as control mechanism between model and data encoding, but it is difficult to find the optimal parameter. In this work, we propose a new inference algorithm that incorporates mutual information (MI), conditional mutual information (CMI), and predictive minimum description length (PMDL) principle to infer gene regulatory networks from DNA microarray data. In this algorithm, the information theoretic quantities MI and CMI determine the regulatory relationships between genes and the PMDL principle method attempts to determine the best MI threshold without the need of a user-specified fine tuning parameter. The performance of the proposed algorithm is evaluated using both synthetic time series data sets and a biological time series data set (Saccharomyces cerevisiae). The results show that the proposed algorithm produced fewer false edges and significantly improved the precision when compared to existing MDL algorithm.

  18. Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria

    Science.gov (United States)

    Teimouri, Hamid; Korkmazhan, Elgin; Stavans, Joel; Levine, Erel

    2017-10-01

    Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.

  19. Liver X Receptor Genes Variants Modulate ALS Phenotype.

    Science.gov (United States)

    Mouzat, Kevin; Molinari, Nicolas; Kantar, Jovana; Polge, Anne; Corcia, Philippe; Couratier, Philippe; Clavelou, Pierre; Juntas-Morales, Raul; Pageot, Nicolas; Lobaccaro, Jean -Marc A; Raoul, Cedric; Lumbroso, Serge; Camu, William

    2018-03-01

    Amyotrophic lateral sclerosis (ALS) is one of the most severe motor neuron (MN) disorders in adults. Phenotype of ALS patients is highly variable and may be influenced by modulators of energy metabolism. Recent works have implicated the liver X receptors α and β (LXRs), either in the propagation process of ALS or in the maintenance of MN survival. LXRs are nuclear receptors activated by oxysterols, modulating cholesterol levels, a suspected modulator of ALS severity. In a cohort of 438 ALS patients and 330 healthy controls, the influence of LXR genes on ALS risk and phenotype was studied using single nucleotide polymorphisms (SNPs). The two LXRα SNPs rs2279238 and rs7120118 were shown to be associated with age at onset in ALS patients. Consistently, homozygotes were twice more correlated than were heterozygotes to delayed onset. The onset was thus delayed by 3.9 years for rs2279238 C/T carriers and 7.8 years for T/T carriers. Similar results were obtained for rs7120118 (+2.1 years and +6.7 years for T/C and C/C genotypes, respectively). The LXRβ SNP rs2695121 was also shown to be associated with a 30% increase of ALS duration (p = 0.0055, FDR = 0.044). The tested genotypes were not associated with ALS risk. These findings add further evidence to the suspected implication of LXR genes in the disease process of ALS and might open new perspectives in ALS therapeutics.

  20. An approach for reduction of false predictions in reverse engineering of gene regulatory networks.

    Science.gov (United States)

    Khan, Abhinandan; Saha, Goutam; Pal, Rajat Kumar

    2018-05-14

    A gene regulatory network discloses the regulatory interactions amongst genes, at a particular condition of the human body. The accurate reconstruction of such networks from time-series genetic expression data using computational tools offers a stiff challenge for contemporary computer scientists. This is crucial to facilitate the understanding of the proper functioning of a living organism. Unfortunately, the computational methods produce many false predictions along with the correct predictions, which is unwanted. Investigations in the domain focus on the identification of as many correct regulations as possible in the reverse engineering of gene regulatory networks to make it more reliable and biologically relevant. One way to achieve this is to reduce the number of incorrect predictions in the reconstructed networks. In the present investigation, we have proposed a novel scheme to decrease the number of false predictions by suitably combining several metaheuristic techniques. We have implemented the same using a dataset ensemble approach (i.e. combining multiple datasets) also. We have employed the proposed methodology on real-world experimental datasets of the SOS DNA Repair network of Escherichia coli and the IMRA network of Saccharomyces cerevisiae. Subsequently, we have experimented upon somewhat larger, in silico networks, namely, DREAM3 and DREAM4 Challenge networks, and 15-gene and 20-gene networks extracted from the GeneNetWeaver database. To study the effect of multiple datasets on the quality of the inferred networks, we have used four datasets in each experiment. The obtained results are encouraging enough as the proposed methodology can reduce the number of false predictions significantly, without using any supplementary prior biological information for larger gene regulatory networks. It is also observed that if a small amount of prior biological information is incorporated here, the results improve further w.r.t. the prediction of true positives

  1. Comparison of Five Major Trichome Regulatory Genes in Brassica villosa with Orthologues within the Brassicaceae

    Science.gov (United States)

    Nayidu, Naghabushana K.; Kagale, Sateesh; Taheri, Ali; Withana-Gamage, Thushan S.; Parkin, Isobel A. P.; Sharpe, Andrew G.; Gruber, Margaret Y.

    2014-01-01

    Coding sequences for major trichome regulatory genes, including the positive regulators GLABRA 1(GL1), GLABRA 2 (GL2), ENHANCER OF GLABRA 3 (EGL3), and TRANSPARENT TESTA GLABRA 1 (TTG1) and the negative regulator TRIPTYCHON (TRY), were cloned from wild Brassica villosa, which is characterized by dense trichome coverage over most of the plant. Transcript (FPKM) levels from RNA sequencing indicated much higher expression of the GL2 and TTG1 regulatory genes in B. villosa leaves compared with expression levels of GL1 and EGL3 genes in either B. villosa or the reference genome species, glabrous B. oleracea; however, cotyledon TTG1 expression was high in both species. RNA sequencing and Q-PCR also revealed an unusual expression pattern for the negative regulators TRY and CPC, which were much more highly expressed in trichome-rich B. villosa leaves than in glabrous B. oleracea leaves and in glabrous cotyledons from both species. The B. villosa TRY expression pattern also contrasted with TRY expression patterns in two diploid Brassica species, and with the Arabidopsis model for expression of negative regulators of trichome development. Further unique sequence polymorphisms, protein characteristics, and gene evolution studies highlighted specific amino acids in GL1 and GL2 coding sequences that distinguished glabrous species from hairy species and several variants that were specific for each B. villosa gene. Positive selection was observed for GL1 between hairy and non-hairy plants, and as expected the origin of the four expressed positive trichome regulatory genes in B. villosa was predicted to be from B. oleracea. In particular the unpredicted expression patterns for TRY and CPC in B. villosa suggest additional characterization is needed to determine the function of the expanded families of trichome regulatory genes in more complex polyploid species within the Brassicaceae. PMID:24755905

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

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    Ehsan Sharif-Paghaleh

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

  3. Direct activation of EXPANSIN14 by LBD18 in the gene regulatory network of lateral root formation in Arabidopsis.

    Science.gov (United States)

    Kim, Jungmook; Lee, Han Woo

    2013-02-01

    Root system architecture is important for plants to adapt to a changing environment. The major determinant of the root system is lateral roots originating from the primary root. The developmental process of lateral root formation can be divided into priming, initiation, primordium development and the emergence of lateral roots, and is well characterized in Arabidopsis. The hormone auxin plays a critical role in lateral root development, and several auxin response modules involving AUXIN RESPONSE FACTORS (ARFs), transcriptional regulators of auxin-regulated genes and Aux/IAA, negative regulators of ARFs, regulate lateral root formation. The LATERAL ORGAN BOUNDARIES DOMAIN/ASYMMETRIC LEAVES2-LIKE (LBD/ASL) gene family encodes a unique class of transcription factors harbouring a conserved plant-specific lateral organ boundary domain and plays a role in lateral organ development of plants including lateral root formation. In our previous study, we showed that LBD18 stimulates lateral root formation in combination with LBD16 downstream of ARF7 and ARF19 during the auxin response. We have recently demonstrated that LBD18 activates expression of EXP14, a gene encoding the cell-wall loosening factor, by directly binding to the EXP14 promoter to promote lateral root emergence. Here we present the molecular function of LBD18 and its gene regulatory network during lateral root formation.

  4. The transcriptional and gene regulatory network of Lactococcus lactis MG1363 during growth in milk.

    Directory of Open Access Journals (Sweden)

    Anne de Jong

    Full Text Available 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.

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

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    Lien Huang-Chun

    2009-03-01

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

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

    Science.gov (United States)

    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.

  7. Omics for Investigating Chitosan as an Antifungal and Gene Modulator

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    Federico Lopez-Moya

    2016-03-01

    Full Text Available Chitosan is a biopolymer with a wide range of applications. The use of chitosan in clinical medicine to control infections by fungal pathogens such as Candida spp. is one of its most promising applications in view of the reduced number of antifungals available. Chitosan increases intracellular oxidative stress, then permeabilizes the plasma membrane of sensitive filamentous fungus Neurospora crassa and yeast. Transcriptomics reveals plasma membrane homeostasis and oxidative metabolism genes as key players in the response of fungi to chitosan. A lipase and a monosaccharide transporter, both inner plasma membrane proteins, and a glutathione transferase are main chitosan targets in N. crassa. Biocontrol fungi such as Pochonia chlamydosporia have a low content of polyunsaturated free fatty acids in their plasma membranes and are resistant to chitosan. Genome sequencing of P. chlamydosporia reveals a wide gene machinery to degrade and assimilate chitosan. Chitosan increases P. chlamydosporia sporulation and enhances parasitism of plant parasitic nematodes by the fungus. Omics studies allow understanding the mode of action of chitosan and help its development as an antifungal and gene modulator.

  8. Contact inhibition and interferon (IFN)-modulated gene expression

    Energy Technology Data Exchange (ETDEWEB)

    Kulesh, D.A.

    1986-01-01

    The relationship between cell morphology, proliferation and contact inhibition was studied in normal and malignant human cells which varied in their sensitivity to contact inhibition. Their ability to proliferate was examined under conditions where the cells were constrained into different shapes. Cell proliferation was quantitated by labeling indices, which were inferred by autoradiography, and by total cell counts. The normal cells (JHU-1, IMR-90) were dependent on cell shape for proliferation capability while the transformed cells (RT4, HT1080) were shape-dependent for proliferation. Interferon (IFN) induced shape-dependent proliferation and contact inhibition in the transformed cells when used at subantiproliferative concentrations. This ability of B-IFN to confer a level of proliferation control which is characteristic of normal fibroblasts suggests a possible relationship between gene expression mediated by IFN and those genes involved in the maintenance of regulated cell proliferation. To evaluate this possibility, cDNA libraries were constructed from IFN-treated and untreated HT1080 cells. The resulting 10 IFN-induced and 11 IFN-repressed sequences were then differentially rescreened using /sup 32/P-cDNA probes. This screening resulted in the identification of at least four cDNA sequences which appeared to be proliferation regulated as well as IFN-modulated. These cloned, regulated cDNA sequences were then used as /sup 32/P-labeled probes to study both the gene expression at the mRNA level employing Northern blotting and slot blotting techniques.

  9. Does positive selection drive transcription factor binding site turnover? A test with Drosophila cis-regulatory modules.

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    Bin Z He

    2011-04-01

    Full Text Available Transcription factor binding site(s (TFBS gain and loss (i.e., turnover is a well-documented feature of cis-regulatory module (CRM evolution, yet little attention has been paid to the evolutionary force(s driving this turnover process. The predominant view, motivated by its widespread occurrence, emphasizes the importance of compensatory mutation and genetic drift. Positive selection, in contrast, although it has been invoked in specific instances of adaptive gene expression evolution, has not been considered as a general alternative to neutral compensatory evolution. In this study we evaluate the two hypotheses by analyzing patterns of single nucleotide polymorphism in the TFBS of well-characterized CRM in two closely related Drosophila species, Drosophila melanogaster and Drosophila simulans. An important feature of the analysis is classification of TFBS mutations according to the direction of their predicted effect on binding affinity, which allows gains and losses to be evaluated independently along the two phylogenetic lineages. The observed patterns of polymorphism and divergence are not compatible with neutral evolution for either class of mutations. Instead, multiple lines of evidence are consistent with contributions of positive selection to TFBS gain and loss as well as purifying selection in its maintenance. In discussion, we propose a model to reconcile the finding of selection driving TFBS turnover with constrained CRM function over long evolutionary time.

  10. DNA methylation affects the lifespan of honey bee (Apis mellifera L.) workers - Evidence for a regulatory module that involves vitellogenin expression but is independent of juvenile hormone function.

    Science.gov (United States)

    Cardoso-Júnior, Carlos A M; Guidugli-Lazzarini, Karina R; Hartfelder, Klaus

    2018-01-01

    The canonic regulatory module for lifespan of honey bee (Apis mellifera) workers involves a mutual repressor relationship between juvenile hormone (JH) and vitellogenin (Vg). Compared to vertebrates, however, little is known about a possible role of epigenetic factors. The full genomic repertoire of DNA methyltransferases (DNMTs) makes the honey bee an attractive emergent model for studying the role of epigenetics in the aging process of invertebrates, and especially so in social insects. We first quantified the transcript levels of the four DNMTs encoding genes in the head thorax and abdomens of workers of different age, showing that dnmt1a and dnmt3 expression is up-regulated in abdomens of old workers, whereas dnmt1b and dnmt2 are down-regulated in heads of old workers. Pharmacological genome demethylation by RG108 treatment caused an increase in worker lifespan. Next, we showed that the genomic DNA methylation status indirectly affects vitellogenin gene expression both in vitro and in vivo in young workers, and that this occurs independent of caloric restriction or JH levels, suggesting that a non-canonical circuitry may be acting in parallel with the JH/Vg module to regulate the adult life cycle of honey bee workers. Our data provide evidence that epigenetic factors play a role in regulatory networks associated with complex life history traits of a social insect. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Chemmangattuvalappil Nishanth

    2012-09-01

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

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

    International Nuclear Information System (INIS)

    Tabbaa, Omar P; Jayaprakash, C

    2014-01-01

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

  13. Analysis of a Gene Regulatory Cascade Mediating Circadian Rhythm in Zebrafish

    Science.gov (United States)

    Wang, Haifang; Du, Jiulin; Yan, Jun

    2013-01-01

    In the study of circadian rhythms, it has been a puzzle how a limited number of circadian clock genes can control diverse aspects of physiology. Here we investigate circadian gene expression genome-wide using larval zebrafish as a model system. We made use of a spatial gene expression atlas to investigate the expression of circadian genes in various tissues and cell types. Comparison of genome-wide circadian gene expression data between zebrafish and mouse revealed a nearly anti-phase relationship and allowed us to detect novel evolutionarily conserved circadian genes in vertebrates. We identified three groups of zebrafish genes with distinct responses to light entrainment: fast light-induced genes, slow light-induced genes, and dark-induced genes. Our computational analysis of the circadian gene regulatory network revealed several transcription factors (TFs) involved in diverse aspects of circadian physiology through transcriptional cascade. Of these, microphthalmia-associated transcription factor a (mitfa), a dark-induced TF, mediates a circadian rhythm of melanin synthesis, which may be involved in zebrafish's adaptation to daily light cycling. Our study describes a systematic method to discover previously unidentified TFs involved in circadian physiology in complex organisms. PMID:23468616

  14. Characterization of regulatory pathways in Xylella fastidiosa: genes and phenotypes controlled by algU.

    Science.gov (United States)

    Shi, Xiang Yang; Dumenyo, C Korsi; Hernandez-Martinez, Rufina; Azad, Hamid; Cooksey, Donald A

    2007-11-01

    Many virulence genes in plant bacterial pathogens are coordinately regulated by "global" regulatory genes. Conducting DNA microarray analysis of bacterial mutants of such genes, compared with the wild type, can help to refine the list of genes that may contribute to virulence in bacterial pathogens. The regulatory gene algU, with roles in stress response and regulation of the biosynthesis of the exopolysaccharide alginate in Pseudomonas aeruginosa and many other bacteria, has been extensively studied. The role of algU in Xylella fastidiosa, the cause of Pierce's disease of grapevines, was analyzed by mutation and whole-genome microarray analysis to define its involvement in aggregation, biofilm formation, and virulence. In this study, an algU::nptII mutant had reduced cell-cell aggregation, attachment, and biofilm formation and lower virulence in grapevines. Microarray analysis showed that 42 genes had significantly lower expression in the algU::nptII mutant than in the wild type. Among these are several genes that could contribute to cell aggregation and biofilm formation, as well as other physiological processes such as virulence, competition, and survival.

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

    Science.gov (United States)

    Mitchison, A

    1997-01-01

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

  16. Dopamine Receptor Genes Modulate Associative Memory in Old Age.

    Science.gov (United States)

    Papenberg, Goran; Becker, Nina; Ferencz, Beata; Naveh-Benjamin, Moshe; Laukka, Erika J; Bäckman, Lars; Brehmer, Yvonne

    2017-02-01

    Previous research shows that associative memory declines more than item memory in aging. Although the underlying mechanisms of this selective impairment remain poorly understood, animal and human data suggest that dopaminergic modulation may be particularly relevant for associative binding. We investigated the influence of dopamine (DA) receptor genes on item and associative memory in a population-based sample of older adults (n = 525, aged 60 years), assessed with a face-scene item associative memory task. The effects of single-nucleotide polymorphisms of DA D1 (DRD1; rs4532), D2 (DRD2/ANKK1/Taq1A; rs1800497), and D3 (DRD3/Ser9Gly; rs6280) receptor genes were examined and combined into a single genetic score. Individuals carrying more beneficial alleles, presumably associated with higher DA receptor efficacy (DRD1 C allele; DRD2 A2 allele; DRD3 T allele), performed better on associative memory than persons with less beneficial genotypes. There were no effects of these genes on item memory or other cognitive measures, such as working memory, executive functioning, fluency, and perceptual speed, indicating a selective association between DA genes and associative memory. By contrast, genetic risk for Alzheimer disease (AD) was associated with worse item and associative memory, indicating adverse effects of APOE ε4 and a genetic risk score for AD (PICALM, BIN1, CLU) on episodic memory in general. Taken together, our results suggest that DA may be particularly important for associative memory, whereas AD-related genetic variations may influence overall episodic memory in older adults without dementia.

  17. Identification of sparsely distributed clusters of cis-regulatory elements in sets of co-expressed genes

    OpenAIRE

    Kreiman, Gabriel

    2004-01-01

    Sequence information and high‐throughput methods to measure gene expression levels open the door to explore transcriptional regulation using computational tools. Combinatorial regulation and sparseness of regulatory elements throughout the genome allow organisms to control the spatial and temporal patterns of gene expression. Here we study the organization of cis‐regulatory elements in sets of co‐regulated genes. We build an algorithm to search for combinations of transcription factor binding...

  18. Bifidobacterium breve - HT-29 cell line interaction: modulation of TNF-α induced gene expression.

    Science.gov (United States)

    Boesten, R J; Schuren, F H J; Willemsen, L E M; Vriesema, A; Knol, J; De Vos, W M

    2011-06-01

    To provide insight in the molecular basis for intestinal host-microbe interactions, we determined the genome-wide transcriptional response of human intestinal epithelial cells following exposure to cells of Bifidobacterium breve. To select an appropriate test system reflecting inflammatory conditions, the responsiveness to TNF-α was compared in T84, Caco-2 and HT-29 cells. The highest TNF-α response was observed in HT-29 cells and this cell line was selected for exposure to the B. breve strains M-16V, NR246 and UCC2003. After one hour of bacterial pre-incubation followed by two hours of additional TNF-α stimulation, B. breve M-16V (86%), but to a much lesser extent strains NR246 (50%) or UCC2003 (32%), showed a strain-specific reduction of the HT-29 transcriptional response to the inflammatory treatment. The most important functional groups of genes that were transcriptionally suppressed by the presence of B. breve M-16V, were found to be involved in immune regulation and apoptotic processes. About 54% of the TNF-α induced genes were solely suppressed by the presence of B. breve M-16V. These included apoptosis-related cysteine protease caspase 7 (CASP7), interferon regulatory factor 3 (IRF3), amyloid beta (A4) precursor proteinbinding family A member 1 (APBA1), NADPH oxidase (NOX5), and leukemia inhibitory factor receptor (LIFR). The extracellular IL-8 concentration was determined by an immunological assay but did not change significantly, indicating that B. breve M-16V only partially modulates the TNF-α pathway. In conclusion, this study shows that B. breve strains modulate gene expression in HT-29 cells under inflammatory conditions in a strain-specific way.

  19. A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer

    Directory of Open Access Journals (Sweden)

    Mary Qu Yang

    Full Text Available Clear cell renal cell carcinoma (ccRCC is the most common and most aggressive form of renal cell cancer (RCC. The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1, as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways. Keywords: ccRCC, Causative mutation, Pathways, Protein-protein interaction, Gene module, eQTL

  20. Both positive and negative regulatory elements mediate expression of a photoregulated CAB gene from Nicotiana plumbaginifolia.

    Science.gov (United States)

    Castresana, C; Garcia-Luque, I; Alonso, E; Malik, V S; Cashmore, A R

    1988-01-01

    We have analyzed promoter regulatory elements from a photoregulated CAB gene (Cab-E) isolated from Nicotiana plumbaginifolia. These studies have been performed by introducing chimeric gene constructs into tobacco cells via Agrobacterium tumefaciens-mediated transformation. Expression studies on the regenerated transgenic plants have allowed us to characterize three positive and one negative cis-acting elements that influence photoregulated expression of the Cab-E gene. Within the upstream sequences we have identified two positive regulatory elements (PRE1 and PRE2) which confer maximum levels of photoregulated expression. These sequences contain multiple repeated elements related to the sequence-ACCGGCCCACTT-. We have also identified within the upstream region a negative regulatory element (NRE) extremely rich in AT sequences, which reduces the level of gene expression in the light. We have defined a light regulatory element (LRE) within the promoter region extending from -396 to -186 bp which confers photoregulated expression when fused to a constitutive nopaline synthase ('nos') promoter. Within this region there is a 132-bp element, extending from -368 to -234 bp, which on deletion from the Cab-E promoter reduces gene expression from high levels to undetectable levels. Finally, we have demonstrated for a full length Cab-E promoter conferring high levels of photoregulated expression, that sequences proximal to the Cab-E TATA box are not replaceable by corresponding sequences from a 'nos' promoter. This contrasts with the apparent equivalence of these Cab-E and 'nos' TATA box-proximal sequences in truncated promoters conferring low levels of photoregulated expression. Images PMID:2901343

  1. A comparative study of covariance selection models for the inference of gene regulatory networks.

    Science.gov (United States)

    Stifanelli, Patrizia F; Creanza, Teresa M; Anglani, Roberto; Liuzzi, Vania C; Mukherjee, Sayan; Schena, Francesco P; Ancona, Nicola

    2013-10-01

    The inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. In this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) 'ℓ(2C)' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ℓ(2C) outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. Software implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip. Copyright © 2013 The Authors. Published by

  2. CD4+CD25+ regulatory T cells control CD8+ T-cell effector differentiation by modulating IL-2 homeostasis

    Science.gov (United States)

    McNally, Alice; Hill, Geoffrey R.; Sparwasser, Tim; Thomas, Ranjeny; Steptoe, Raymond J.

    2011-01-01

    CD4+CD25+ regulatory T cells (Treg) play a crucial role in the regulation of immune responses. Although many mechanisms of Treg suppression in vitro have been described, the mechanisms by which Treg modulate CD8+ T cell differentiation and effector function in vivo are more poorly defined. It has been proposed, in many instances, that modulation of cytokine homeostasis could be an important mechanism by which Treg regulate adaptive immunity; however, direct experimental evidence is sparse. Here we demonstrate that CD4+CD25+ Treg, by critically regulating IL-2 homeostasis, modulate CD8+ T-cell effector differentiation. Expansion and effector differentiation of CD8+ T cells is promoted by autocrine IL-2 but, by competing for IL-2, Treg limit CD8+ effector differentiation. Furthermore, a regulatory loop exists between Treg and CD8+ effector T cells, where IL-2 produced during CD8+ T-cell effector differentiation promotes Treg expansion. PMID:21502514

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

    Directory of Open Access Journals (Sweden)

    Farré Domènec

    2007-12-01

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

  4. Evolutionary changes of Hox genes and relevant regulatory factors provide novel insights into mammalian morphological modifications.

    Science.gov (United States)

    Li, Kui; Sun, Xiaohui; Chen, Meixiu; Sun, Yingying; Tian, Ran; Wang, Zhengfei; Xu, Shixia; Yang, Guang

    2018-01-01

    The diversity of body plans of mammals accelerates the innovation of lifestyles and the extensive adaptation to different habitats, including terrestrial, aerial and aquatic habitats. However, the genetic basis of those phenotypic modifications, which have occurred during mammalian evolution, remains poorly explored. In the present study, we synthetically surveyed the evolutionary pattern of Hox clusters that played a powerful role in the morphogenesis along the head-tail axis of animal embryos and the main regulatory factors (Mll, Bmi1 and E2f6) that control the expression of Hox genes. A deflected density of repetitive elements and lineage-specific radical mutations of Mll have been determined in marine mammals with morphological changes, suggesting that evolutionary changes may alter Hox gene expression in these lineages, leading to the morphological modification of these lineages. Although no positive selection was detected at certain ancestor nodes of lineages, the increased ω values of Hox genes implied the relaxation of functional constraints of these genes during the mammalian evolutionary process. More importantly, 49 positively-selected sites were identified in mammalian lineages with phenotypic modifications, indicating adaptive evolution acting on Hox genes and regulatory factors. In addition, 3 parallel amino acid substitutions in some Hox genes were examined in marine mammals, which might be responsible for their streamlined body. © 2017 The Authors. Integrative Zoology published by International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

  5. DNA-binding site of major regulatory protein alpha 4 specifically associated with promoter-regulatory domains of alpha genes of herpes simplex virus type 1.

    OpenAIRE

    Kristie, T M; Roizman, B

    1986-01-01

    Herpes simplex virus type 1 genes form at least five groups (alpha, beta 1, beta 2, gamma 1, and gamma 2) whose expression is coordinately regulated and sequentially ordered in a cascade fashion. Previous studies have shown that functional alpha 4 gene product is essential for the transition from alpha to beta protein synthesis and have suggested that alpha 4 gene expression is autoregulatory. We have previously reported that labeled DNA fragments containing promoter-regulatory domains of thr...

  6. Dynamic and modular gene regulatory networks drive the development of gametogenesis.

    Science.gov (United States)

    Che, Dongxue; Wang, Yang; Bai, Weiyang; Li, Leijie; Liu, Guiyou; Zhang, Liangcai; Zuo, Yongchun; Tao, Shiheng; Hua, Jinlian; Liao, Mingzhi

    2017-07-01

    Gametogenesis is a complex process, which includes mitosis and meiosis and results in the production of ovum and sperm. The development of gametogenesis is dynamic and needs many different genes to work synergistically, but it is lack of global perspective research about this process. In this study, we detected the dynamic process of gametogenesis from the perspective of systems biology based on protein-protein interaction networks (PPINs) and functional analysis. Results showed that gametogenesis genes have strong synergistic effects in PPINs within and between different phases during the development. Addition to the synergistic effects on molecular networks, gametogenesis genes showed functional consistency within and between different phases, which provides the further evidence about the dynamic process during the development of gametogenesis. At last, we detected and provided the core molecular modules of different phases about gametogenesis. The gametogenesis genes and related modules can be obtained from our Web site Gametogenesis Molecule Online (GMO, http://gametsonline.nwsuaflmz.com/index.php), which is freely accessible. GMO may be helpful for the reference and application of these genes and modules in the future identification of key genes about gametogenesis. Summary, this work provided a computational perspective and frame to the analysis of the gametogenesis dynamics and modularity in both human and mouse. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  7. Lactobacillus reuteri-specific immunoregulatory gene rsiR modulates histamine production and immunomodulation by Lactobacillus reuteri.

    Science.gov (United States)

    Hemarajata, P; Gao, C; Pflughoeft, K J; Thomas, C M; Saulnier, D M; Spinler, J K; Versalovic, J

    2013-12-01

    Human microbiome-derived strains of Lactobacillus reuteri potently suppress proinflammatory cytokines like human tumor necrosis factor (TNF) by converting the amino acid l-histidine to the biogenic amine histamine. Histamine suppresses mitogen-activated protein (MAP) kinase activation and cytokine production by signaling via histamine receptor type 2 (H2) on myeloid cells. Investigations of the gene expression profiles of immunomodulatory L. reuteri ATCC PTA 6475 highlighted numerous genes that were highly expressed during the stationary phase of growth, when TNF suppression is most potent. One such gene was found to be a regulator of genes involved in histidine-histamine metabolism by this probiotic species. During the course of these studies, this gene was renamed the Lactobacillus reuteri-specific immunoregulatory (rsiR) gene. The rsiR gene is essential for human TNF suppression by L. reuteri and expression of the histidine decarboxylase (hdc) gene cluster on the L. reuteri chromosome. Inactivation of rsiR resulted in diminished TNF suppression in vitro and reduced anti-inflammatory effects in vivo in a trinitrobenzene sulfonic acid (TNBS)-induced mouse model of acute colitis. A L. reuteri strain lacking an intact rsiR gene was unable to suppress colitis and resulted in greater concentrations of serum amyloid A (SAA) in the bloodstream of affected animals. The PhdcAB promoter region targeted by rsiR was defined by reporter gene experiments. These studies support the presence of a regulatory gene, rsiR, which modulates the expression of a gene cluster known to mediate immunoregulation by probiotics at the transcriptional level. These findings may point the way toward new strategies for controlling gene expression in probiotics by dietary interventions or microbiome manipulation.

  8. GRN2SBML: automated encoding and annotation of inferred gene regulatory networks complying with SBML.

    Science.gov (United States)

    Vlaic, Sebastian; Hoffmann, Bianca; Kupfer, Peter; Weber, Michael; Dräger, Andreas

    2013-09-01

    GRN2SBML automatically encodes gene regulatory networks derived from several inference tools in systems biology markup language. Providing a graphical user interface, the networks can be annotated via the simple object access protocol (SOAP)-based application programming interface of BioMart Central Portal and minimum information required in the annotation of models registry. Additionally, we provide an R-package, which processes the output of supported inference algorithms and automatically passes all required parameters to GRN2SBML. Therefore, GRN2SBML closes a gap in the processing pipeline between the inference of gene regulatory networks and their subsequent analysis, visualization and storage. GRN2SBML is freely available under the GNU Public License version 3 and can be downloaded from http://www.hki-jena.de/index.php/0/2/490. General information on GRN2SBML, examples and tutorials are available at the tool's web page.

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

    Science.gov (United States)

    Oka, Ayako; Shiroishi, Toshihiko

    2014-01-01

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

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

    Science.gov (United States)

    Meier, Daniel; Schindler, Detlev

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Daniel Meier

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

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

    Science.gov (United States)

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

    2016-06-01

    Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Degnan Bernard M

    2011-01-01

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

  14. Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

    Directory of Open Access Journals (Sweden)

    Xiao Chang

    Full Text Available BACKGROUND: The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. METHODOLOGY/PRINCIPAL FINDINGS: In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A, and secondary metabolism is induced when the growth is slowed down (phase B. Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. CONCLUSIONS: This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies

  15. Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.

    Science.gov (United States)

    Chang, Xiao; Liu, Shuai; Yu, Yong-Tao; Li, Yi-Xue; Li, Yuan-Yuan

    2010-08-12

    The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization. In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected. This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.

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

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    Flavia Vischi Winck

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

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

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    Tuqyah Abdullah Al Qazlan

    2015-01-01

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

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

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

    2014-01-01

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

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

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

    2017-01-05

    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. Copyright © 2017 Pritchard et al.

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

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    Victoria L. Pritchard

    2017-01-01

    Full Text Available 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.

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

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    Joeri Ruyssinck

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

  2. Identifying cis-regulatory modules by combining comparative and compositional analysis of DNA.

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    Pierstorff, Nora; Bergman, Casey M; Wiehe, Thomas

    2006-12-01

    Predicting cis-regulatory modules (CRMs) in higher eukaryotes is a challenging computational task. Commonly used methods to predict CRMs based on the signal of transcription factor binding sites (TFBS) are limited by prior information about transcription factor specificity. More general methods that bypass the reliance on TFBS models are needed for comprehensive CRM prediction. We have developed a method to predict CRMs called CisPlusFinder that identifies high density regions of perfect local ungapped sequences (PLUSs) based on multiple species conservation. By assuming that PLUSs contain core TFBS motifs that are locally overrepresented, the method attempts to capture the expected features of CRM structure and evolution. Applied to a benchmark dataset of CRMs involved in early Drosophila development, CisPlusFinder predicts more annotated CRMs than all other methods tested. Using the REDfly database, we find that some 'false positive' predictions in the benchmark dataset correspond to recently annotated CRMs. Our work demonstrates that CRM prediction methods that combine comparative genomic data with statistical properties of DNA may achieve reasonable performance when applied genome-wide in the absence of an a priori set of known TFBS motifs. The program CisPlusFinder can be downloaded at http://jakob.genetik.uni-koeln.de/bioinformatik/people/nora/nora.html. All software is licensed under the Lesser GNU Public License (LGPL).

  3. The Macrophage Galactose-Type C-Type Lectin (MGL Modulates Regulatory T Cell Functions.

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    Ilaria Grazia Zizzari

    Full Text Available Regulatory T cells (Tregs are physiologically designed to prevent autoimmune disease and maintain self-tolerance. In tumour microenvironments, their presence is related to a poor prognosis, and they influence the therapeutic outcome due to their capacity to suppress the immune response by cell-cell contact and to release immunosuppressive cytokines. In this study, we demonstrate that Treg immunosuppressive activity can be modulated by the cross-linking between the CD45RA expressed by Tregs and the C-type lectin MGL. This specific interaction strongly decreases the immunosuppressive activity of Tregs, restoring the proliferative capacity of co-cultured T lymphocytes. This effect can be attributed to changes in CD45RA and TCR signalling through the inhibition of Lck and inactivation of Zap-70, an increase in the Foxp3 methylation status and, ultimately, the reduced production of suppressive cytokines. These results indicate a role of MGL as an immunomodulator within the tumour microenvironment interfering with Treg functions, suggesting its possible use in the design of anticancer vaccines.

  4. Heterologous expression of the Aspergillus nidulans regulatory gene nirA in Fusarium oxysporum.

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    Daboussi, M J; Langin, T; Deschamps, F; Brygoo, Y; Scazzocchio, C; Burger, G

    1991-12-20

    We have isolated strains of Fusarium oxysporum carrying mutations conferring a phenotype characteristic of a loss of function in the regulatory gene of nitrate assimilation (nirA in Aspergillus nidulans, nit-4 in Neurospora crassa). One of these nir- mutants was successfully transformed with a plasmid containing the nirA gene of A. nidulans. The nitrate reductase of the transformants is still inducible, although the maximum activity is lower than in the wild type. Single and multiple integration events were found, as well as a strict correlation between the presence of the nirA gene and the Nir+ phenotype of the F. oxysporum transformants. We also investigated how the A. nidulans structural gene (niaD) is regulated in F. oxysporum. Enzyme assays and Northern experiments show that the niaD gene is subject to nitrate induction and that it responds to nitrogen metabolite repression in a F. oxysporum genetic background. This indicates that both the mechanisms of specific induction, mediated by a gene product isofunctional to nirA, and nitrogen metabolite repression, presumably mediated by a gene product isofunctional to the homologous gene of A. nidulans, are operative in F. oxysporum.

  5. Gene Module Identification from Microarray Data Using Nonnegative Independent Component Analysis

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    Ting Gong

    2007-01-01

    Full Text Available Genes mostly interact with each other to form transcriptional modules for performing single or multiple functions. It is important to unravel such transcriptional modules and to determine how disturbances in them may lead to disease. Here, we propose a non-negative independent component analysis (nICA approach for transcriptional module discovery. nICA method utilizes the non-negativity constraint to enforce the independence of biological processes within the participated genes. In such, nICA decomposes the observed gene expression into positive independent components, which fi ts better to the reality of corresponding putative biological processes. In conjunction with nICA modeling, visual statistical data analyzer (VISDA is applied to group genes into modules in latent variable space. We demonstrate the usefulness of the approach through the identification of composite modules from yeast data and the discovery of pathway modules in muscle regeneration.

  6. Integration of Genome-Wide TF Binding and Gene Expression Data to Characterize Gene Regulatory Networks in Plant Development.

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    Chen, Dijun; Kaufmann, Kerstin

    2017-01-01

    Key transcription factors (TFs) controlling the morphogenesis of flowers and leaves have been identified in the model plant Arabidopsis thaliana. Recent genome-wide approaches based on chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) enable systematic identification of genome-wide TF binding sites (TFBSs) of these regulators. Here, we describe a computational pipeline for analyzing ChIP-seq data to identify TFBSs and to characterize gene regulatory networks (GRNs) with applications to the regulatory studies of flower development. In particular, we provide step-by-step instructions on how to download, analyze, visualize, and integrate genome-wide data in order to construct GRNs for beginners of bioinformatics. The practical guide presented here is ready to apply to other similar ChIP-seq datasets to characterize GRNs of interest.

  7. Toward understanding the evolution of vertebrate gene regulatory networks: comparative genomics and epigenomic approaches.

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    Martinez-Morales, Juan R

    2016-07-01

    Vertebrates, as most animal phyla, originated >500 million years ago during the Cambrian explosion, and progressively radiated into the extant classes. Inferring the evolutionary history of the group requires understanding the architecture of the developmental programs that constrain the vertebrate anatomy. Here, I review recent comparative genomic and epigenomic studies, based on ChIP-seq and chromatin accessibility, which focus on the identification of functionally equivalent cis-regulatory modules among species. This pioneer work, primarily centered in the mammalian lineage, has set the groundwork for further studies in representative vertebrate and chordate species. Mapping of active regulatory regions across lineages will shed new light on the evolutionary forces stabilizing ancestral developmental programs, as well as allowing their variation to sustain morphological adaptations on the inherited vertebrate body plan. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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

    Science.gov (United States)

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

    2013-03-21

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

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

    NARCIS (Netherlands)

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

    2016-01-01

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

  10. Kynurenine 3-Monooxygenase Gene Associated With Nicotine Initiation and Addiction: Analysis of Novel Regulatory Features at 5′ and 3′-Regions

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    Hassan A. Aziz

    2018-06-01

    Full Text Available Tobacco smoking is widespread behavior in Qatar and worldwide and is considered one of the major preventable causes of ill health and death. Nicotine is part of tobacco smoke that causes numerous health risks and is incredibly addictive; it binds to the α7 nicotinic acetylcholine receptor (α7nAChR in the brain. Recent studies showed α7nAChR involvement in the initiation and addiction of smoking. Kynurenic acid (KA, a significant tryptophan metabolite, is an antagonist of α7nAChR. Inhibition of kynurenine 3-monooxygenase enzyme encoded by KMO enhances the KA levels. Modulating KMO gene expression could be a useful tactic for the treatment of tobacco initiation and dependence. Since KMO regulation is still poorly understood, we aimed to investigate the 5′ and 3′-regulatory factors of KMO gene to advance our knowledge to modulate KMO gene expression. In this study, bioinformatics methods were used to identify the regulatory sequences associated with expression of KMO. The displayed differential expression of KMO mRNA in the same tissue and different tissues suggested the specific usage of the KMO multiple alternative promoters. Eleven KMO alternative promoters identified at 5′-regulatory region contain TATA-Box, lack CpG Island (CGI and showed dinucleotide base-stacking energy values specific to transcription factor binding sites (TFBSs. The structural features of regulatory sequences can influence the transcription process and cell type-specific expression. The uncharacterized LOC105373233 locus coding for non-coding RNA (ncRNA located on the reverse strand in a convergent manner at the 3′-side of KMO locus. The two genes likely expressed by a promoter that lacks TATA-Box harbor CGI and two TFBSs linked to the bidirectional transcription, the NRF1, and ZNF14 motifs. We identified two types of microRNA (miR in the uncharacterized LOC105373233 ncRNA, which are like hsa-miR-5096 and hsa-miR-1285-3p and can target the miR recognition

  11. Transcriptional Regulation in Ebola Virus: Effects of Gene Border Structure and Regulatory Elements on Gene Expression and Polymerase Scanning Behavior.

    Science.gov (United States)

    Brauburger, Kristina; Boehmann, Yannik; Krähling, Verena; Mühlberger, Elke

    2016-02-15

    The highly pathogenic Ebola virus (EBOV) has a nonsegmented negative-strand (NNS) RNA genome containing seven genes. The viral genes either are separated by intergenic regions (IRs) of variable length or overlap. The structure of the EBOV gene overlaps is conserved throughout all filovirus genomes and is distinct from that of the overlaps found in other NNS RNA viruses. Here, we analyzed how diverse gene borders and noncoding regions surrounding the gene borders influence transcript levels and govern polymerase behavior during viral transcription. Transcription of overlapping genes in EBOV bicistronic minigenomes followed the stop-start mechanism, similar to that followed by IR-containing gene borders. When the gene overlaps were extended, the EBOV polymerase was able to scan the template in an upstream direction. This polymerase feature seems to be generally conserved among NNS RNA virus polymerases. Analysis of IR-containing gene borders showed that the IR sequence plays only a minor role in transcription regulation. Changes in IR length were generally well tolerated, but specific IR lengths led to a strong decrease in downstream gene expression. Correlation analysis revealed that these effects were largely independent of the surrounding gene borders. Each EBOV gene contains exceptionally long untranslated regions (UTRs) flanking the open reading frame. Our data suggest that the UTRs adjacent to the gene borders are the main regulators of transcript levels. A highly complex interplay between the different cis-acting elements to modulate transcription was revealed for specific combinations of IRs and UTRs, emphasizing the importance of the noncoding regions in EBOV gene expression control. Our data extend those from previous analyses investigating the implication of noncoding regions at the EBOV gene borders for gene expression control. We show that EBOV transcription is regulated in a highly complex yet not easily predictable manner by a set of interacting cis

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

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    Junhua Li

    2014-01-01

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

  13. A novel method for predicting activity of cis-regulatory modules, based on a diverse training set.

    Science.gov (United States)

    Yang, Wei; Sinha, Saurabh

    2017-01-01

    With the rapid emergence of technologies for locating cis-regulatory modules (CRMs) genome-wide, the next pressing challenge is to assign precise functions to each CRM, i.e. to determine the spatiotemporal domains or cell-types where it drives expression. A popular approach to this task is to model the typical k-mer composition of a set of CRMs known to drive a common expression pattern, and assign that pattern to other CRMs exhibiting a similar k-mer composition. This approach does not rely on prior knowledge of transcription factors relevant to the CRM or their binding motifs, and is thus more widely applicable than motif-based methods for predicting CRM activity, but is also prone to false positive predictions. We present a novel strategy to improve the above-mentioned approach: to predict if a CRM drives a specific gene expression pattern, assess not only how similar the CRM is to other CRMs with similar activity but also to CRMs with distinct activities. We use a state-of-the-art statistical method to quantify a CRM's sequence similarity to many different training sets of CRMs, and employ a classification algorithm to integrate these similarity scores into a single prediction of the CRM's activity. This strategy is shown to significantly improve CRM activity prediction over current approaches. Our implementation of the new method, called IMMBoost, is freely available as source code, at https://github.com/weiyangedward/IMMBoost CONTACT: sinhas@illinois.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. big bang gene modulates gut immune tolerance in Drosophila.

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    Bonnay, François; Cohen-Berros, Eva; Hoffmann, Martine; Kim, Sabrina Y; Boulianne, Gabrielle L; Hoffmann, Jules A; Matt, Nicolas; Reichhart, Jean-Marc

    2013-02-19

    Chronic inflammation of the intestine is detrimental to mammals. Similarly, constant activation of the immune response in the gut by the endogenous flora is suspected to be harmful to Drosophila. Therefore, the innate immune response in the gut of Drosophila melanogaster is tightly balanced to simultaneously prevent infections by pathogenic microorganisms and tolerate the endogenous flora. Here we describe the role of the big bang (bbg) gene, encoding multiple membrane-associated PDZ (PSD-95, Discs-large, ZO-1) domain-containing protein isoforms, in the modulation of the gut immune response. We show that in the adult Drosophila midgut, BBG is present at the level of the septate junctions, on the apical side of the enterocytes. In the absence of BBG, these junctions become loose, enabling the intestinal flora to trigger a constitutive activation of the anterior midgut immune response. This chronic epithelial inflammation leads to a reduced lifespan of bbg mutant flies. Clearing the commensal flora by antibiotics prevents the abnormal activation of the gut immune response and restores a normal lifespan. We now provide genetic evidence that Drosophila septate junctions are part of the gut immune barrier, a function that is evolutionarily conserved in mammals. Collectively, our data suggest that septate junctions are required to maintain the subtle balance between immune tolerance and immune response in the Drosophila gut, which represents a powerful model to study inflammatory bowel diseases.

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

    Science.gov (United States)

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

    2013-09-12

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

  16. An Organismal Model for Gene Regulatory Networks in the Gut-Associated Immune Response

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    Katherine M. Buckley

    2017-10-01

    Full Text Available The gut epithelium is an ancient site of complex communication between the animal immune system and the microbial world. While elements of self-non-self receptors and effector mechanisms differ greatly among animal phyla, some aspects of recognition, regulation, and response are broadly conserved. A gene regulatory network (GRN approach provides a means to investigate the nature of this conservation and divergence even as more peripheral functional details remain incompletely understood. The sea urchin embryo is an unparalleled experimental model for detangling the GRNs that govern embryonic development. By applying this theoretical framework to the free swimming, feeding larval stage of the purple sea urchin, it is possible to delineate the conserved regulatory circuitry that regulates the gut-associated immune response. This model provides a morphologically simple system in which to efficiently unravel regulatory connections that are phylogenetically relevant to immunity in vertebrates. Here, we review the organism-wide cellular and transcriptional immune response of the sea urchin larva. A large set of transcription factors and signal systems, including epithelial expression of interleukin 17 (IL17, are important mediators in the activation of the early gut-associated response. Many of these have homologs that are active in vertebrate immunity, while others are ancient in animals but absent in vertebrates or specific to echinoderms. This larval model provides a means to experimentally characterize immune function encoded in the sea urchin genome and the regulatory interconnections that control immune response and resolution across the tissues of the organism.

  17. Network statistics of genetically-driven gene co-expression modules in mouse crosses

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    Marie-Pier eScott-Boyer

    2013-12-01

    Full Text Available In biology, networks are used in different contexts as ways to represent relationships between entities, such as for instance interactions between genes, proteins or metabolites. Despite progress in the analysis of such networks and their potential to better understand the collective impact of genes on complex traits, one remaining challenge is to establish the biologic validity of gene co-expression networks and to determine what governs their organization. We used WGCNA to construct and analyze seven gene expression datasets from several tissues of mouse recombinant inbred strains (RIS. For six out of the 7 networks, we found that linkage to module QTLs (mQTLs could be established for 29.3% of gene co-expression modules detected in the several mouse RIS. For about 74.6% of such genetically-linked modules, the mQTL was on the same chromosome as the one contributing most genes to the module, with genes originating from that chromosome showing higher connectivity than other genes in the modules. Such modules (that we considered as genetically-driven had network statistic properties (density, centralization and heterogeneity that set them apart from other modules in the network. Altogether, a sizeable portion of gene co-expression modules detected in mouse RIS panels had genetic determinants as their main organizing principle. In addition to providing a biologic interpretation validation for these modules, these genetic determinants imparted on them particular properties that set them apart from other modules in the network, to the point that they can be predicted to a large extent on the basis of their network statistics.

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

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    Xin Lai

    2013-01-01

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

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

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    Yali Wang

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

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

    Science.gov (United States)

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

    2012-01-01

    Taking into account the complexity and technical specificity of advanced therapy medicinal products: (gene and cell therapy medicinal products and tissue engineered products), a dedicated European regulatory framework was needed. Regulation (EC) No. 1394/2007, the "ATMP Regulation" provides tailored regulatory principles for the evaluation and authorization of these innovative medicines. The majority of gene or cell therapy product development is carried out by academia, hospitals, and small- and medium-sized enterprises (SMEs). Thus, acknowledging the particular needs of these types of sponsors, the legislation also provides incentives for product development tailored to them. The European Medicines Agency (EMA) and, in particular, its Committee for Advanced Therapies (CAT) provide a variety of opportunities for early interaction with developers of ATMPs to enable them to have early regulatory and scientific input. An important tool to promote innovation and the development of new medicinal products by micro-, small-, and medium-sized enterprises is the EMA's SME initiative launched in December 2005 to offer financial and administrative assistance to smaller companies. The European legislation also foresees the involvement of stakeholders, such as patient organizations, in the development of new medicines. Considering that gene therapy medicinal products are developed in many cases for treatment of rare diseases often of monogenic origin, the involvement of patient organizations, which focus on rare diseases and genetic and congenital disorders, is fruitful. Two such organizations are represented in the CAT. Research networks play another important role in the development of gene therapy medicinal products. The European Commission is funding such networks through the EU Sixth Framework Program. Copyright © 2012 Elsevier Inc. All rights reserved.

  1. 5' Region of the human interleukin 4 gene: structure and potential regulatory elements

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    Eder, A; Krafft-Czepa, H; Krammer, P H

    1988-01-25

    The lymphokine Interleukin 4 (IL-4) is secreted by antigen or mitogen activated T lymphocytes. IL-4 stimulates activation and differentiation of B lymphocytes and growth of T lymphocytes and mast cells. The authors isolated the human IL-4 gene from a lambda EMBL3 genomic library. As a probe they used a synthetic oligonucleotide spanning position 40 to 79 of the published IL-4 cDNA sequence. The 5' promoter region contains several sequence elements which may have a cis-acting regulatory function for IL-4 gene expression. These elements include a TATA-box, three CCAAT-elements (two are on the non-coding strand) and an octamer motif. A comparison of the 5' flanking region of the human murine IL-4 gene (4) shows that the region between position -306 and +44 is highly conserved (83% homology).

  2. Evolution of hepatic glucose metabolism: liver-specific glucokinase deficiency explained by parallel loss of the gene for glucokinase regulatory protein (GCKR.

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    Zhao Yang Wang

    Full Text Available Glucokinase (GCK plays an important role in the regulation of carbohydrate metabolism. In the liver, phosphorylation of glucose to glucose-6-phosphate by GCK is the first step for both glycolysis and glycogen synthesis. However, some vertebrate species are deficient in GCK activity in the liver, despite containing GCK genes that appear to be compatible with function in their genomes. Glucokinase regulatory protein (GCKR is the most important post-transcriptional regulator of GCK in the liver; it participates in the modulation of GCK activity and location depending upon changes in glucose levels. In experimental models, loss of GCKR has been shown to associate with reduced hepatic GCK protein levels and activity.GCKR genes and GCKR-like sequences were identified in the genomes of all vertebrate species with available genome sequences. The coding sequences of GCKR and GCKR-like genes were identified and aligned; base changes likely to disrupt coding potential or splicing were also identified.GCKR genes could not be found in the genomes of 9 vertebrate species, including all birds. In addition, in multiple mammalian genomes, whereas GCKR-like gene sequences could be identified, these genes could not predict a functional protein. Vertebrate species that were previously reported to be deficient in hepatic GCK activity were found to have deleted (birds and lizard or mutated (mammals GCKR genes. Our results suggest that mutation of the GCKR gene leads to hepatic GCK deficiency due to the loss of the stabilizing effect of GCKR.

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

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    Elvezia Maria Paraboschi

    2015-09-01

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

  4. Endogenous adaptation to low oxygen modulates T-cell regulatory pathways in EAE.

    Science.gov (United States)

    Esen, Nilufer; Katyshev, Vladimir; Serkin, Zakhar; Katysheva, Svetlana; Dore-Duffy, Paula

    2016-01-19

    In the brain, chronic inflammatory activity may lead to compromised delivery of oxygen and glucose suggesting that therapeutic approaches aimed at restoring metabolic balance may be useful. In vivo exposure to chronic mild normobaric hypoxia (10 % oxygen) leads to a number of endogenous adaptations that includes vascular remodeling (angioplasticity). Angioplasticity promotes tissue survival. We have previously shown that induction of adaptive angioplasticity modulates the disease pattern in myelin oligodendrocyte glycoprotein (MOG)-induced experimental autoimmune encephalomyelitis (EAE). In the present study, we define mechanisms by which adaptation to low oxygen functionally ameliorates the signs and symptoms of EAE and for the first time show that tissue hypoxia may fundamentally alter neurodegenerative disease. C57BL/6 mice were immunized with MOG, and some of them were kept in the hypoxia chambers (day 0) and exposed to 10 % oxygen for 3 weeks, while the others were kept at normoxic environment. Sham-immunized controls were included in both hypoxic and normoxic groups. Animals were sacrificed at pre-clinical and peak disease periods for tissue collection and analysis. Exposure to mild hypoxia decreased histological evidence of inflammation. Decreased numbers of cluster of differentiation (CD)4+ T cells were found in the hypoxic spinal cords associated with a delayed Th17-specific cytokine response. Hypoxia-induced changes did not alter the sensitization of peripheral T cells to the MOG peptide. Exposure to mild hypoxia induced significant increases in anti-inflammatory IL-10 levels and an increase in the number of spinal cord CD25+FoxP3+ T-regulatory cells. Acclimatization to mild hypoxia incites a number of endogenous adaptations that induces an anti-inflammatory milieu. Further understanding of these mechanisms system may pinpoint possible new therapeutic targets to treat neurodegenerative disease.

  5. Boolean Dynamic Modeling Approaches to Study Plant Gene Regulatory Networks: Integration, Validation, and Prediction.

    Science.gov (United States)

    Velderraín, José Dávila; Martínez-García, Juan Carlos; Álvarez-Buylla, Elena R

    2017-01-01

    Mathematical models based on dynamical systems theory are well-suited tools for the integration of available molecular experimental data into coherent frameworks in order to propose hypotheses about the cooperative regulatory mechanisms driving developmental processes. Computational analysis of the proposed models using well-established methods enables testing the hypotheses by contrasting predictions with observations. Within such framework, Boolean gene regulatory network dynamical models have been extensively used in modeling plant development. Boolean models are simple and intuitively appealing, ideal tools for collaborative efforts between theorists and experimentalists. In this chapter we present protocols used in our group for the study of diverse plant developmental processes. We focus on conceptual clarity and practical implementation, providing directions to the corresponding technical literature.

  6. Vitamin A and feeding statuses modulate the insulin-regulated gene expression in Zucker lean and fatty primary rat hepatocytes.

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    Wei Chen

    Full Text Available Unattended hepatic insulin resistance predisposes individuals to dyslipidemia, type 2 diabetes and many other metabolic complications. The mechanism of hepatic insulin resistance at the gene expression level remains unrevealed. To examine the effects of vitamin A (VA, total energy intake and feeding conditions on the insulin-regulated gene expression in primary hepatocytes of Zucker lean (ZL and fatty (ZF rats, we analyze the expression levels of hepatic model genes in response to the treatments of insulin and retinoic acid (RA. We report that the insulin- and RA-regulated glucokinase, sterol regulatory element-binding protein-1c and cytosolic form of phosphoenolpyruvate carboxykinase expressions are impaired in hepatocytes of ZF rats fed chow or a VA sufficient (VAS diet ad libitum. The impairments are partially corrected when ZF rats are fed a VA deficient (VAD diet ad libitum or pair-fed a VAS diet to the intake of their VAD counterparts in non-fasting conditions. Interestingly in the pair-fed ZL and ZF rats, transient overeating on the last day of pair-feeding regimen changes the expression levels of some VA catabolic genes, and impairs the insulin- and RA-regulated gene expression in hepatocytes. These results demonstrate that VA and feeding statuses modulate the hepatic insulin sensitivity at the gene expression level.

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

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    Min Kyung Sung

    2014-12-01

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

  8. [Analysis of cis-regulatory element distribution in gene promoters of Gossypium raimondii and Arabidopsis thaliana].

    Science.gov (United States)

    Sun, Gao-Fei; He, Shou-Pu; Du, Xiong-Ming

    2013-10-01

    Cotton genomic studies have boomed since the release of Gossypium raimondii draft genome. In this study, cis-regulatory element (CRE) in 1 kb length sequence upstream 5' UTR of annotated genes were selected and scanned in the Arabidopsis thaliana (At) and Gossypium raimondii (Gr) genomes, based on the database of PLACE (Plant cis-acting Regulatory DNA Elements). According to the definition of this study, 44 (12.3%) and 57 (15.5%) CREs presented "peak-like" distribution in the 1 kb selected sequences of both genomes, respectively. Thirty-four of them were peak-like distributed in both genomes, which could be further categorized into 4 types based on their core sequences. The coincidence of TATABOX peak position and their actual position ((-) -30 bp) indicated that the position of a common CRE was conservative in different genes, which suggested that the peak position of these CREs was their possible actual position of transcription factors. The position of a common CRE was also different between the two genomes due to stronger length variation of 5' UTR in Gr than At. Furthermore, most of the peak-like CREs were located in the region of -110 bp-0 bp, which suggested that concentrated distribution might be conductive to the interaction of transcription factors, and then regulate the gene expression in downstream.

  9. Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

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    Kim Man-Sun

    2012-05-01

    Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

  10. Reprogramming of gene expression during compression wood formation in pine: Coordinated modulation of S-adenosylmethionine, lignin and lignan related genes

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    Villalobos David P

    2012-06-01

    Full Text Available Abstract Background Transcript profiling of differentiating secondary xylem has allowed us to draw a general picture of the genes involved in wood formation. However, our knowledge is still limited about the regulatory mechanisms that coordinate and modulate the different pathways providing substrates during xylogenesis. The development of compression wood in conifers constitutes an exceptional model for these studies. Although differential expression of a few genes in differentiating compression wood compared to normal or opposite wood has been reported, the broad range of features that distinguish this reaction wood suggest that the expression of a larger set of genes would be modified. Results By combining the construction of different cDNA libraries with microarray analyses we have identified a total of 496 genes in maritime pine (Pinus pinaster, Ait. that change in expression during differentiation of compression wood (331 up-regulated and 165 down-regulated compared to opposite wood. Samples from different provenances collected in different years and geographic locations were integrated into the analyses to mitigate the effects of multiple sources of variability. This strategy allowed us to define a group of genes that are consistently associated with compression wood formation. Correlating with the deposition of a thicker secondary cell wall that characterizes compression wood development, the expression of a number of genes involved in synthesis of cellulose, hemicellulose, lignin and lignans was up-regulated. Further analysis of a set of these genes involved in S-adenosylmethionine metabolism, ammonium recycling, and lignin and lignans biosynthesis showed changes in expression levels in parallel to the levels of lignin accumulation in cells undergoing xylogenesis in vivo and in vitro. Conclusions The comparative transcriptomic analysis reported here have revealed a broad spectrum of coordinated transcriptional modulation of genes

  11. Reprogramming of gene expression during compression wood formation in pine: Coordinated modulation of S-adenosylmethionine, lignin and lignan related genes

    Science.gov (United States)

    2012-01-01

    Background Transcript profiling of differentiating secondary xylem has allowed us to draw a general picture of the genes involved in wood formation. However, our knowledge is still limited about the regulatory mechanisms that coordinate and modulate the different pathways providing substrates during xylogenesis. The development of compression wood in conifers constitutes an exceptional model for these studies. Although differential expression of a few genes in differentiating compression wood compared to normal or opposite wood has been reported, the broad range of features that distinguish this reaction wood suggest that the expression of a larger set of genes would be modified. Results By combining the construction of different cDNA libraries with microarray analyses we have identified a total of 496 genes in maritime pine (Pinus pinaster, Ait.) that change in expression during differentiation of compression wood (331 up-regulated and 165 down-regulated compared to opposite wood). Samples from different provenances collected in different years and geographic locations were integrated into the analyses to mitigate the effects of multiple sources of variability. This strategy allowed us to define a group of genes that are consistently associated with compression wood formation. Correlating with the deposition of a thicker secondary cell wall that characterizes compression wood development, the expression of a number of genes involved in synthesis of cellulose, hemicellulose, lignin and lignans was up-regulated. Further analysis of a set of these genes involved in S-adenosylmethionine metabolism, ammonium recycling, and lignin and lignans biosynthesis showed changes in expression levels in parallel to the levels of lignin accumulation in cells undergoing xylogenesis in vivo and in vitro. Conclusions The comparative transcriptomic analysis reported here have revealed a broad spectrum of coordinated transcriptional modulation of genes involved in biosynthesis of

  12. Isoeugenol monooxygenase and its putative regulatory gene are located in the eugenol metabolic gene cluster in Pseudomonas nitroreducens Jin1.

    Science.gov (United States)

    Ryu, Ji-Young; Seo, Jiyoung; Unno, Tatsuya; Ahn, Joong-Hoon; Yan, Tao; Sadowsky, Michael J; Hur, Hor-Gil

    2010-03-01

    The plant-derived phenylpropanoids eugenol and isoeugenol have been proposed as useful precursors for the production of natural vanillin. Genes involved in the metabolism of eugenol and isoeugenol were clustered in region of about a 30 kb of Pseudomonas nitroreducens Jin1. Two of the 23 ORFs in this region, ORFs 26 (iemR) and 27 (iem), were predicted to be involved in the conversion of isoeugenol to vanillin. The deduced amino acid sequence of isoeugenol monooxygenase (Iem) of strain Jin1 had 81.4% identity to isoeugenol monooxygenase from Pseudomonas putida IE27, which also transforms isoeugenol to vanillin. Iem was expressed in E. coli BL21(DE3) and was found to lead to isoeugenol to vanillin transformation. Deletion and cloning analyses indicated that the gene iemR, located upstream of iem, is required for expression of iem in the presence of isoeugenol, suggesting it to be the iem regulatory gene. Reverse transcription, real-time PCR analyses indicated that the genes involved in the metabolism of eugenol and isoeugenol were differently induced by isoeugenol, eugenol, and vanillin.

  13. From gene engineering to gene modulation and manipulation: can we prevent or detect gene doping in sports?

    Science.gov (United States)

    Fischetto, Giuseppe; Bermon, Stéphane

    2013-10-01

    During the last 2 decades, progress in deciphering the human gene map as well as the discovery of specific defective genes encoding particular proteins in some serious human diseases have resulted in attempts to treat sick patients with gene therapy. There has been considerable focus on human recombinant proteins which were gene-engineered and produced in vitro (insulin, growth hormone, insulin-like growth factor-1, erythropoietin). Unfortunately, these substances and methods also became improper tools for unscrupulous athletes. Biomedical research has focused on the possible direct insertion of gene material into the body, in order to replace some defective genes in vivo and/or to promote long-lasting endogenous synthesis of deficient proteins. Theoretically, diabetes, anaemia, muscular dystrophies, immune deficiency, cardiovascular diseases and numerous other illnesses could benefit from such innovative biomedical research, though much work remains to be done. Considering recent findings linking specific genotypes and physical performance, it is tempting to submit the young athletic population to genetic screening or, alternatively, to artificial gene expression modulation. Much research is already being conducted in order to achieve a safe transfer of genetic material to humans. This is of critical importance since uncontrolled production of the specifically coded protein, with serious secondary adverse effects (polycythaemia, acute cardiovascular problems, cancer, etc.), could occur. Other unpredictable reactions (immunogenicity of vectors or DNA-vector complex, autoimmune anaemia, production of wild genetic material) also remain possible at the individual level. Some new substances (myostatin blockers or anti-myostatin antibodies), although not gene material, might represent a useful and well-tolerated treatment to prevent progression of muscular dystrophies. Similarly, other molecules, in the roles of gene or metabolic activators [5-aminoimidazole-4

  14. Evaluation of artificial time series microarray data for dynamic gene regulatory network inference.

    Science.gov (United States)

    Xenitidis, P; Seimenis, I; Kakolyris, S; Adamopoulos, A

    2017-08-07

    High-throughput technology like microarrays is widely used in the inference of gene regulatory networks (GRNs). We focused on time series data since we are interested in the dynamics of GRNs and the identification of dynamic networks. We evaluated the amount of information that exists in artificial time series microarray data and the ability of an inference process to produce accurate models based on them. We used dynamic artificial gene regulatory networks in order to create artificial microarray data. Key features that characterize microarray data such as the time separation of directly triggered genes, the percentage of directly triggered genes and the triggering function type were altered in order to reveal the limits that are imposed by the nature of microarray data on the inference process. We examined the effect of various factors on the inference performance such as the network size, the presence of noise in microarray data, and the network sparseness. We used a system theory approach and examined the relationship between the pole placement of the inferred system and the inference performance. We examined the relationship between the inference performance in the time domain and the true system parameter identification. Simulation results indicated that time separation and the percentage of directly triggered genes are crucial factors. Also, network sparseness, the triggering function type and noise in input data affect the inference performance. When two factors were simultaneously varied, it was found that variation of one parameter significantly affects the dynamic response of the other. Crucial factors were also examined using a real GRN and acquired results confirmed simulation findings with artificial data. Different initial conditions were also used as an alternative triggering approach. Relevant results confirmed that the number of datasets constitutes the most significant parameter with regard to the inference performance. Copyright © 2017 Elsevier

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

    Science.gov (United States)

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

    2016-03-01

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

  16. Characterization of chemically induced liver injuries using gene co-expression modules.

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    Gregory J Tawa

    Full Text Available Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1 known biochemical pathways associated with liver injuries and 2 clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20% genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.

  17. Potential energy landscape and robustness of a gene regulatory network: toggle switch.

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    Keun-Young Kim

    2007-03-01

    Full Text Available Finding a multidimensional potential landscape is the key for addressing important global issues, such as the robustness of cellular networks. We have uncovered the underlying potential energy landscape of a simple gene regulatory network: a toggle switch. This was realized by explicitly constructing the steady state probability of the gene switch in the protein concentration space in the presence of the intrinsic statistical fluctuations due to the small number of proteins in the cell. We explored the global phase space for the system. We found that the protein synthesis rate and the unbinding rate of proteins to the gene were small relative to the protein degradation rate; the gene switch is monostable with only one stable basin of attraction. When both the protein synthesis rate and the unbinding rate of proteins to the gene are large compared with the protein degradation rate, two global basins of attraction emerge for a toggle switch. These basins correspond to the biologically stable functional states. The potential energy barrier between the two basins determines the time scale of conversion from one to the other. We found as the protein synthesis rate and protein unbinding rate to the gene relative to the protein degradation rate became larger, the potential energy barrier became larger. This also corresponded to systems with less noise or the fluctuations on the protein numbers. It leads to the robustness of the biological basins of the gene switches. The technique used here is general and can be applied to explore the potential energy landscape of the gene networks.

  18. THD-Module Extractor: An Application for CEN Module Extraction and Interesting Gene Identification for Alzheimer's Disease.

    Science.gov (United States)

    Kakati, Tulika; Kashyap, Hirak; Bhattacharyya, Dhruba K

    2016-11-30

    There exist many tools and methods for construction of co-expression network from gene expression data and for extraction of densely connected gene modules. In this paper, a method is introduced to construct co-expression network and to extract co-expressed modules having high biological significance. The proposed method has been validated on several well known microarray datasets extracted from a diverse set of species, using statistical measures, such as p and q values. The modules obtained in these studies are found to be biologically significant based on Gene Ontology enrichment analysis, pathway analysis, and KEGG enrichment analysis. Further, the method was applied on an Alzheimer's disease dataset and some interesting genes are found, which have high semantic similarity among them, but are not significantly correlated in terms of expression similarity. Some of these interesting genes, such as MAPT, CASP2, and PSEN2, are linked with important aspects of Alzheimer's disease, such as dementia, increase cell death, and deposition of amyloid-beta proteins in Alzheimer's disease brains. The biological pathways associated with Alzheimer's disease, such as, Wnt signaling, Apoptosis, p53 signaling, and Notch signaling, incorporate these interesting genes. The proposed method is evaluated in regard to existing literature.

  19. Computational integration of homolog and pathway gene module expression reveals general stemness signatures.

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    Martina Koeva

    Full Text Available The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.

  20. Modulation and Expression of Tumor Suppressor Genes by Environmental Agents

    National Research Council Canada - National Science Library

    Ostrander, Gary Kent

    1996-01-01

    ... in the retinoblastoma gene in retinoblastoma and hepatocarcinomas following induction with known environmental carcinogens. Studies to date suggest the retinoblastoma gene/protein may play a role in oncogenesis in the medaka.

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

    Science.gov (United States)

    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.

  2. Recurrent neural network based hybrid model for reconstructing gene regulatory network.

    Science.gov (United States)

    Raza, Khalid; Alam, Mansaf

    2016-10-01

    One of the exciting problems in systems biology research is to decipher how genome controls the development of complex biological system. The gene regulatory networks (GRNs) help in the identification of regulatory interactions between genes and offer fruitful information related to functional role of individual gene in a cellular system. Discovering GRNs lead to a wide range of applications, including identification of disease related pathways providing novel tentative drug targets, helps to predict disease response, and also assists in diagnosing various diseases including cancer. Reconstruction of GRNs from available biological data is still an open problem. This paper proposes a recurrent neural network (RNN) based model of GRN, hybridized with generalized extended Kalman filter for weight update in backpropagation through time training algorithm. The RNN is a complex neural network that gives a better settlement between biological closeness and mathematical flexibility to model GRN; and is also able to capture complex, non-linear and dynamic relationships among variables. Gene expression data are inherently noisy and Kalman filter performs well for estimation problem even in noisy data. Hence, we applied non-linear version of Kalman filter, known as generalized extended Kalman filter, for weight update during RNN training. The developed model has been tested on four benchmark networks such as DNA SOS repair network, IRMA network, and two synthetic networks from DREAM Challenge. We performed a comparison of our results with other state-of-the-art techniques which shows superiority of our proposed model. Further, 5% Gaussian noise has been induced in the dataset and result of the proposed model shows negligible effect of noise on results, demonstrating the noise tolerance capability of the model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. Epigenetic Editing: targeted rewriting of epigenetic marks to modulate expression of selected target genes.

    NARCIS (Netherlands)

    de Groote, M.L.; Verschure, P.J.; Rots, M.G.

    2012-01-01

    Despite significant advances made in epigenetic research in recent decades, many questions remain unresolved, especially concerning cause and consequence of epigenetic marks with respect to gene expression modulation (GEM). Technologies allowing the targeting of epigenetic enzymes to predetermined

  4. Epigenetic Editing : targeted rewriting of epigenetic marks to modulate expression of selected target genes

    NARCIS (Netherlands)

    de Groote, Marloes L.; Verschure, Pernette J.; Rots, Marianne G.

    2012-01-01

    Despite significant advances made in epigenetic research in recent decades, many questions remain unresolved, especially concerning cause and consequence of epigenetic marks with respect to gene expression modulation (GEM). Technologies allowing the targeting of epigenetic enzymes to predetermined

  5. Drought response in wheat: key genes and regulatory mechanisms controlling root system architecture and transpiration efficiency

    Science.gov (United States)

    Kulkarni, Manoj; Soolanayakanahally, Raju; Ogawa, Satoshi; Uga, Yusaku; Selvaraj, Michael G.; Kagale, Sateesh

    2017-12-01

    sequence and advent genome editing technologies, are expected to aid in deciphering of the functional roles of genes and regulatory networks underlying adaptive phenological traits, and utilizing the outcomes of such studies in developing drought tolerance cultivars.

  6. A quantitative and dynamic model of the Arabidopsis flowering time gene regulatory network.

    Directory of Open Access Journals (Sweden)

    Felipe Leal Valentim

    Full Text Available Various environmental signals integrate into a network of floral regulatory genes leading to the final decision on when to flower. Although a wealth of qualitative knowledge is available on how flowering time genes regulate each other, only a few studies incorporated this knowledge into predictive models. Such models are invaluable as they enable to investigate how various types of inputs are combined to give a quantitative readout. To investigate the effect of gene expression disturbances on flowering time, we developed a dynamic model for the regulation of flowering time in Arabidopsis thaliana. Model parameters were estimated based on expression time-courses for relevant genes, and a consistent set of flowering times for plants of various genetic backgrounds. Validation was performed by predicting changes in expression level in mutant backgrounds and comparing these predictions with independent expression data, and by comparison of predicted and experimental flowering times for several double mutants. Remarkably, the model predicts that a disturbance in a particular gene has not necessarily the largest impact on directly connected genes. For example, the model predicts that SUPPRESSOR OF OVEREXPRESSION OF CONSTANS (SOC1 mutation has a larger impact on APETALA1 (AP1, which is not directly regulated by SOC1, compared to its effect on LEAFY (LFY which is under direct control of SOC1. This was confirmed by expression data. Another model prediction involves the importance of cooperativity in the regulation of APETALA1 (AP1 by LFY, a prediction supported by experimental evidence. Concluding, our model for flowering time gene regulation enables to address how different quantitative inputs are combined into one quantitative output, flowering time.

  7. Enhanced regulatory gene expressions in the blood and articular cartilage of patients with rheumatoid arthritis

    Directory of Open Access Journals (Sweden)

    Elena Vasilyevna Chetina

    2012-01-01

    Full Text Available Objective: to study the expression ratio of the non-tissue specific regulatory genes mTOR, р21, ATG1, caspase 3, tumor necrosis factor-а (TNF-а, and interleukin-6 (IL-6, as well as matrix metalloproteinase 13 (MMP-13 and X type collagen (COL10A1, cartilage resorption-associated MMP13 and COL10A1 in the blood and knee articular cartilage in patients with rheumatoid arthritis (RA. Subjects and methods. Twenty-five specimens of the distal femoral articular cartilage condyles were studied in 15 RA patients (mean age 52.4+9.1 years after endoprosthetic knee joint replacement and in 10 healthy individuals (mean age 36.0+9.1 years included into the control group. Twenty-eight blood samples taken from 28 RA patients (aged 52+7.6 years prior to endoprosthetic knee joint replacement and 27 blood samples from healthy individuals (mean age 53.6+8.3 years; a control group were also analyzed. Real-time quantitative polymerase chain reaction was applied to estimate the expression of the mTOR, p21, ATG1, caspase 3, TNF-а, IL- 6, COL0A1, and MMP-13 genes. The levels of a protein equivalent in the p70-S6K(activated by mTOR, p21, and caspase 3 genes concerned was measured in the isolated lymphocyte lysates, by applying the commercially available ELISA kits. Total protein in the cell extracts was determined using the Bradford assay procedure. Results. The cartilage samples from patients with end-stage RA exhibited a significantly higher mTOR, ATG1, p21, TNFа, MMP-13, and COL10A1 gene expressions than did those from the healthy individuals. At the same time, IL6 gene expression was much lower than that in the control group. The expressions of the mTOR, ATG1, p21, TNFа, and IL 6 genes in the blood of RA patients were much greater than those in the donors. Caspase 3 expression did not differ essentially in the bloods of the patients with RA and healthy individuals. The bloods failed to show MMP-13 and COL10A1 expressions. High mTOR and p21 gene expressions were

  8. Improving functional modules discovery by enriching interaction networks with gene profiles

    KAUST Repository

    Salem, Saeed

    2013-05-01

    Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

  9. Fusobacterium nucleatum binding to complement regulatory protein CD46 modulates the expression and secretion of cytokines and matrix metalloproteinases by oral epithelial cells.

    Science.gov (United States)

    Mahtout, Hayette; Chandad, Fatiha; Rojo, Jose M; Grenier, Daniel

    2011-02-01

    Periodontitis is a chronic inflammatory disease that results in the destruction of the supporting tissues of the teeth. Gingival epithelial cells are an important mechanical barrier and participate in the host inflammatory response to periodontopathogens. The aim of the present study is to investigate the capacity of Fusobacterium nucleatum to bind to the complement regulatory protein CD46 expressed by oral epithelial cells and to determine the impact of the binding on the gene expression and protein secretion of interleukin (IL)-6, IL-8, and matrix metalloproteinase (MMP)-9 by oral epithelial cells. Binding of recombinant human CD46 to the surface of F. nucleatum was demonstrated by immunologic assays. After stimulation of oral epithelial cells with F. nucleatum, gene expression was determined by real-time polymerase chain reaction analysis while protein secretion was monitored by enzyme-linked immunosorbent assays. Heat and protease treatments of bacterial cells reduced CD46 binding. F. nucleatum-bound CD46 mediated the cleavage of C3b in the presence of factor I. Stimulating oral epithelial cells with F. nucleatum at a multiplicity of infection of 50 resulted in a significant upregulation of the gene expression and protein secretion of IL-6, IL-8, and MMP-9 by oral epithelial cells. However, pretreating the epithelial cells with an anti-CD46 polyclonal antibody attenuated the production of IL-6, IL-8, and MMP-9 in response to F. nucleatum. Such an inhibitory effect was not observed with non-specific antibodies. The present study demonstrates that F. nucleatum can bind the complement regulatory protein CD46. The interaction of F. nucleatum with epithelial cell surface CD46 may contribute to increasing the levels of proinflammatory mediators and MMPs in periodontal sites and consequently modulate tissue destruction.

  10. Neural model of gene regulatory network: a survey on supportive meta-heuristics.

    Science.gov (United States)

    Biswas, Surama; Acharyya, Sriyankar

    2016-06-01

    Gene regulatory network (GRN) is produced as a result of regulatory interactions between different genes through their coded proteins in cellular context. Having immense importance in disease detection and drug finding, GRN has been modelled through various mathematical and computational schemes and reported in survey articles. Neural and neuro-fuzzy models have been the focus of attraction in bioinformatics. Predominant use of meta-heuristic algorithms in training neural models has proved its excellence. Considering these facts, this paper is organized to survey neural modelling schemes of GRN and the efficacy of meta-heuristic algorithms towards parameter learning (i.e. weighting connections) within the model. This survey paper renders two different structure-related approaches to infer GRN which are global structure approach and substructure approach. It also describes two neural modelling schemes, such as artificial neural network/recurrent neural network based modelling and neuro-fuzzy modelling. The meta-heuristic algorithms applied so far to learn the structure and parameters of neutrally modelled GRN have been reviewed here.

  11. Plasticity of the cis-regulatory input function of a gene.

    Directory of Open Access Journals (Sweden)

    Avraham E Mayo

    2006-04-01

    Full Text Available The transcription rate of a gene is often controlled by several regulators that bind specific sites in the gene's cis-regulatory region. The combined effect of these regulators is described by a cis-regulatory input function. What determines the form of an input function, and how variable is it with respect to mutations? To address this, we employ the well-characterized lac operon of Escherichia coli, which has an elaborate input function, intermediate between Boolean AND-gate and OR-gate logic. We mapped in detail the input function of 12 variants of the lac promoter, each with different point mutations in the regulator binding sites, by means of accurate expression measurements from living cells. We find that even a few mutations can significantly change the input function, resulting in functions that resemble Pure AND gates, OR gates, or single-input switches. Other types of gates were not found. The variant input functions can be described in a unified manner by a mathematical model. The model also lets us predict which functions cannot be reached by point mutations. The input function that we studied thus appears to be plastic, in the sense that many of the mutations do not ruin the regulation completely but rather result in new ways to integrate the inputs.

  12. Regulatory sequences driving expression of the sea urchin Otp homeobox gene in oral ectoderm cells.

    Science.gov (United States)

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

    2007-01-01

    PlOtp (Orthopedia), a homeodomain-containing transcription factor, has been recently characterized as a key regulator of the morphogenesis of the skeletal system in the embryo of the sea urchin Paracentrotus lividus. Otp acts as a positive regulator in a subset of oral ectodermal cells which transmit short-range signals to the underlying primary mesenchyme cells where skeletal synthesis is initiated. To shed some light on the molecular mechanisms involved in such a process, we begun a functional analysis of the cis-regulatory sequences of the Otp gene. Congruent with the spatial expression profile of the endogenous Otp gene, we found that while a DNA region from -494 to +358 is shown to drive in vivo GFP reporter expression in the oral ectoderm, but also in the foregut, a larger region spanning from -2044 to +358 is needed to give firmly established tissue specificity. Microinjection of PCR-amplified DNA constructs, truncated in the 5' regulatory region, and determination of GFP mRNA level in injected embryos allowed the identification of a 5'-flanking fragment of 184bp in length, essential for expression of the transgene in the oral ectoderm of pluteus stage embryos. Finally, we conducted DNAse I-footprinting assays in nuclear extracts for the 184bp region and detected two protected sequences. Data bank search indicates that these sites contain consensus binding sites for transcription factors.

  13. Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

    KAUST Repository

    Othoum, Ghofran K

    2013-05-01

    Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

  14. Identifying Regulatory Patterns at the 3'end Regions of Over-expressed and Under-expressed Genes

    KAUST Repository

    Othoum, Ghofran K

    2013-01-01

    Promoters, neighboring regulatory regions and those extending further upstream of the 5’end of genes, are considered one of the main components affecting the expression status of genes in a specific phenotype. More recently research by Chen et al. (2006, 2012) and Mapendano et al. (2010) demonstrated that the 3’end regulatory regions of genes also influence gene expression. However, the association between the regulatory regions surrounding 3’end of genes and their over- or under-expression status in a particular phenotype has not been systematically studied. The aim of this study is to ascertain if regulatory regions surrounding the 3’end of genes contain sufficient regulatory information to correlate genes with their expression status in a particular phenotype. Over- and under-expressed ovarian cancer (OC) genes were used as a model. Exploratory analysis of the 3’end regions were performed by transforming the annotated regions using principal component analysis (PCA), followed by clustering the transformed data thereby achieving a clear separation of genes with different expression status. Additionally, several classification algorithms such as Naïve Bayes, Random Forest and Support Vector Machine (SVM) were tested with different parameter settings to analyze the discriminatory capacity of the 3’end regions of genes related to their gene expression status. The best performance was achieved using the SVM classification model with 10-fold cross-validation that yielded an accuracy of 98.4%, sensitivity of 99.5% and specificity of 92.5%. For gene expression status for newly available instances, based on information derived from the 3’end regions, an SVM predictive model was developed with 10-fold cross-validation that yielded an accuracy of 67.0%, sensitivity of 73.2% and specificity of 61.0%. Moreover, building an SVM with polynomial kernel model to PCA transformed data yielded an accuracy of 83.1%, sensitivity of 92.5% and specificity of 74.8% using

  15. A Meta-Analysis of Multiple Matched Copy Number and Transcriptomics Data Sets for Inferring Gene Regulatory Relationships

    Science.gov (United States)

    Newton, Richard; Wernisch, Lorenz

    2014-01-01

    Inferring gene regulatory relationships from observational data is challenging. Manipulation and intervention is often required to unravel causal relationships unambiguously. However, gene copy number changes, as they frequently occur in cancer cells, might be considered natural manipulation experiments on gene expression. An increasing number of data sets on matched array comparative genomic hybridisation and transcriptomics experiments from a variety of cancer pathologies are becoming publicly available. Here we explore the potential of a meta-analysis of thirty such data sets. The aim of our analysis was to assess the potential of in silico inference of trans-acting gene regulatory relationships from this type of data. We found sufficient correlation signal in the data to infer gene regulatory relationships, with interesting similarities between data sets. A number of genes had highly correlated copy number and expression changes in many of the data sets and we present predicted potential trans-acted regulatory relationships for each of these genes. The study also investigates to what extent heterogeneity between cell types and between pathologies determines the number of statistically significant predictions available from a meta-analysis of experiments. PMID:25148247

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

    Directory of Open Access Journals (Sweden)

    Alexandra Saudemont

    2010-12-01

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

  17. MutaNET: a tool for automated analysis of genomic mutations in gene regulatory networks.

    Science.gov (United States)

    Hollander, Markus; Hamed, Mohamed; Helms, Volkhard; Neininger, Kerstin

    2018-03-01

    Mutations in genomic key elements can influence gene expression and function in various ways, and hence greatly contribute to the phenotype. We developed MutaNET to score the impact of individual mutations on gene regulation and function of a given genome. MutaNET performs statistical analyses of mutations in different genomic regions. The tool also incorporates the mutations in a provided gene regulatory network to estimate their global impact. The integration of a next-generation sequencing pipeline enables calling mutations prior to the analyses. As application example, we used MutaNET to analyze the impact of mutations in antibiotic resistance (AR) genes and their potential effect on AR of bacterial strains. MutaNET is freely available at https://sourceforge.net/projects/mutanet/. It is implemented in Python and supported on Mac OS X, Linux and MS Windows. Step-by-step instructions are available at http://service.bioinformatik.uni-saarland.de/mutanet/. volkhard.helms@bioinformatik.uni-saarland.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  18. Gene Editing of Microalgae: Scientific Progress and Regulatory Challenges in Europe.

    Science.gov (United States)

    Spicer, Andrew; Molnar, Attila

    2018-03-06

    It is abundantly clear that the development of gene editing technologies, represents a potentially powerful force for good with regard to human and animal health and addressing the challenges we continue to face in a growing global population. This now includes the development of approaches to modify microalgal strains for potential improvements in productivity, robustness, harvestability, processability, nutritional composition, and application. The rapid emergence and ongoing developments in this area demand a timely review and revision of the current definitions and regulations around genetically modified organisms (GMOs), particularly within Europe. Current practices within the EU provide exemptions from the GMO directives for organisms, including crop plants and micro-organisms that are produced through chemical or UV/radiation mutagenesis. However, organisms generated through gene editing, including microalgae, where only genetic changes in native genes are made, remain currently under the GMO umbrella; they are, as such, excluded from practical and commercial opportunities in the EU. In this review, we will review the advances that are being made in the area of gene editing in microalgae and the impact of regulation on commercial advances in this area with consideration to the current regulatory framework as it relates to GMOs including GM microalgae in Europe.

  19. Gene dosage compensation calibrates four regulatory RNAs to control Vibrio cholerae quorum sensing

    DEFF Research Database (Denmark)

    Svenningsen, Sine L; Tu, Kimberly C; Bassler, Bonnie L

    2009-01-01

    the quorum regulatory RNAs 1-4 (Qrr1-4). The four Qrr sRNAs are functionally redundant. That is, expression of any one of them is sufficient for wild-type quorum-sensing behaviour. Here, we show that the combined action of two feedback loops, one involving the sRNA-activator LuxO and one involving the sRNA......Quorum sensing is a mechanism of cell-to-cell communication that allows bacteria to coordinately regulate gene expression in response to changes in cell-population density. At the core of the Vibrio cholerae quorum-sensing signal transduction pathway reside four homologous small RNAs (sRNAs), named......-target HapR, promotes gene dosage compensation between the four qrr genes. Gene dosage compensation adjusts the total Qrr1-4 sRNA pool and provides the molecular mechanism underlying sRNA redundancy. The dosage compensation mechanism is exquisitely sensitive to small perturbations in Qrr levels. Precisely...

  20. The diabetes type 1 locus Idd6 modulates activity of CD4+CD25+ regulatory T-cells.

    Science.gov (United States)

    Rogner, Ute Christine; Lepault, Françoise; Gagnerault, Marie-Claude; Vallois, David; Morin, Joëlle; Avner, Philip; Boitard, Christian

    2006-01-01

    The genetic locus Idd6 confers susceptibility to the spontaneous development of type 1 diabetes in the NOD mouse. Our studies on disease resistance of the congenic mouse strain NOD.C3H 6.VIII showed that Idd6 influences T-cell activities in the peripheral immune system and suggest that a major mechanism by which the Idd6 locus modifies diabetes development is via modulation of regulatory T-cell activities. Our transfer experiments using total splenocytes and purified T-cells demonstrated that the locus specifically controls the efficiency of disease protection mediated by the regulatory CD4(+)CD25(+) T-cell subset. Our data also implicate the Idd6 locus in controlling the balance between infiltrating lymphocytes and antigen-presenting cells within the pancreatic islet.

  1. Radiation-modulated gene expression in C. elegans

    International Nuclear Information System (INIS)

    Nelson, G.A.; Bayeta, E.; Perez, C.; Lloyd, E.; Jones, T.; Smith, A.; Tian, J.

    2003-01-01

    Full text: We use the nematode C. elegans to characterize the genotoxic and cytotoxic effects of ionizing radiation with emphasis effects of charged particle radiation and have described the fluence vs. response relationships for mutation, chromosome aberration and certain developmental errors. These endpoints quantify the biological after repair and compensation pathways have completed their work. In order to address the control of these reactions we have turned to gene expression profiling to identify genes that uniquely respond to high LET species or respond differentially as a function of radiation properties. We have employed whole genome microarray methods to map gene expression following exposure to gamma rays, protons and accelerated iron ions. We found that 599 of 17871 genes analyzed showed differential expression 3 hrs after exposure to 3 Gy of at least one radiation types. 193 were up-regulated, 406 were down-regulated, and 90% were affected by only one species of radiation. Genes whose transcription levels responded significantly mapped to definite statistical clusters that were unique for each radiation type. We are now trying to establish the functional relationships of the genes their relevance to mitigation of radiation-induced damage. Three approaches are being used. First, bioinformatics tools are being used to determine the roles of genes in co-regulated gene sets. Second, we are applying the technique of RNA interference to determine whether our radiation-induced genes affect cell survival (measured in terms of embryo survival) and chromosome aberration (intestinal anaphase bridges). Finally we are focussing on the response of the most strongly-regulated gene in our data set. This is the autosomal gene, F36D3.9, whose predicted structure is that of a cysteine protease resembling cathepsin B. An enzymological approach is being used to characterize this gene at the protein level. This work was supported by NASA Cooperative Agreement NCC9-149

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

    Directory of Open Access Journals (Sweden)

    Liang Jinghang

    2012-08-01

    Full Text Available Abstract Background Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs. As a logical model, probabilistic Boolean networks (PBNs consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n or O(nN2n for a sparse matrix. Results This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN. An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n, where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a

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

    Directory of Open Access Journals (Sweden)

    Faridah Hani Mohamed Salleh

    2017-01-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  5. MicroRNA-related genetic variants in iron regulatory genes, dietary iron intake, microRNAs and lung cancer risk.

    Science.gov (United States)

    Zhang, L; Ye, Y; Tu, H; Hildebrandt, M A; Zhao, L; Heymach, J V; Roth, J A; Wu, X

    2017-05-01

    Genetic variations in MicroRNA (miRNA) binding sites may alter structural accessibility of miRNA binding sites to modulate risk of cancer. This large-scale integrative multistage study was aimed to evaluate the interplay of genetic variations in miRNA binding sites of iron regulatory pathway, dietary iron intake and lung cancer (LC) risk. The interplay of genetic variant, dietary iron intake and LC risk was assessed in large-scale case-control study. Functional characterization of the validated SNP and analysis of target miRNAs were performed. We found that the miRNA binding site SNP rs1062980 in 3' UTR of Iron-Responsive Element Binding protein 2 gene (IREB2) was associated with a 14% reduced LC risk (P value = 4.9×10 - 9). Comparing to AA genotype, GG genotype was associated with a 27% reduced LC risk. This association was evident in males and ever-smokers but not in females and never-smokers. Higher level of dietary iron intake was significantly associated with 39% reduced LC risk (P value = 2.0×10 - 8). This association was only present in individuals with AG + AA genotypes with a 46% reduced risk (P value = 1.0×10 - 10), but not in GG genotype. The eQTL-analysis showed that rs1062980 significantly alters IREB2 expression level. Rs1062980 is predicted to alter a miR-29 binding site on IREB2 and indeed the expression of miR-29 is inversely correlated with IREB2 expression. Further, we found that higher circulating miR-29a level was significantly associated with 78% increased LC risk. The miRNA binding site SNP rs1062980 in iron regulatory pathway, which may alter the expression of IREB2 potentially through modulating the binding of miR-29a, together with dietary iron intake may modify risk of LC both individually and jointly. These discoveries reveal novel pathway for understanding lung cancer tumorigenesis and risk stratification. © The Author 2017. Published by Oxford University Press on behalf of the European Society for

  6. Context dependent regulatory patterns of the androgen receptor and androgen receptor target genes

    International Nuclear Information System (INIS)

    Olsen, Jan Roger; Azeem, Waqas; Hellem, Margrete Reime; Marvyin, Kristo; Hua, Yaping; Qu, Yi; Li, Lisha; Lin, Biaoyang; Ke, XI- Song; Øyan, Anne Margrete; Kalland, Karl- Henning

    2016-01-01

    inducing androgen-dependent transcription of AR target genes, suggesting the importance of missing cofactor(s). Regulatory mechanisms of AR and androgen-dependent AR target gene transcription are insufficiently understood and may be critical for prostate cancer initiation, progression and escape from standard therapy. The present model is useful for the study of context dependent activation of the AR and its transcriptome. The online version of this article (doi:10.1186/s12885-016-2453-4) contains supplementary material, which is available to authorized users

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

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    Dozmorov Igor

    2007-05-01

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

  8. Characterization of the bovine pregnancy-associated glycoprotein gene family – analysis of gene sequences, regulatory regions within the promoter and expression of selected genes

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    Walker Angela M

    2009-04-01

    Full Text Available Abstract Background The Pregnancy-associated glycoproteins (PAGs belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1 we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2 we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3 we determined relative transcript abundance of selected PAGs during pregnancy and, 4 we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo PAG-2. Results From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs, were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed

  9. Identification of Autophagy-Related Genes and Their Regulatory miRNAs Associated with Celiac Disease in Children

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    Sergio Comincini

    2017-02-01

    Full Text Available Celiac disease (CD is a severe genetic autoimmune disorder, affecting about one in 100 people, where the ingestion of gluten leads to damage in the small intestine. Diagnosing CD is quite complex and requires blood tests and intestinal biopsy examinations. Controversy exists regarding making the diagnosis without biopsy, due to the large spectrum of manifesting symptoms; furthermore, small-intestinal gastroscopy examinations have a relatively complex management in the pediatric population. To identify novel molecular markers useful to increase the sensitivity and specificity in the diagnosis of pediatric CD patients, the expression levels of two key autophagy executor genes (ATG7 and BECN1 and their regulatory validated miRNAs (miR-17 and miR-30a, respectively were analyzed by relative quantitative real-time-PCR on a cohort of confirmed CD patients compared to age-related controls. Among the investigated targets, the non-parametric Mann–Whitney U test and ROC analysis indicated the highest significant association of BECN1 with CD status in the blood, while in intestinal biopsies, all of the investigated sequences were positively associated with CD diagnosis. Nomogram-based analysis showed nearly opposite expression trends in blood compared to intestine tissue, while hierarchical clustering dendrograms enabled identifying CD and control subgroups based on specific genes and miRNA expression signatures. Next, using an established in vitro approach, through digested gliadin administration in Caco-2 cells, we also highlighted that the modulation of miR-17 endogenous levels using enriched exosomes increased the intracellular autophagosome content, thereby altering the autophagic status. Altogether, these results highlighted novel molecular markers that might be useful to increase the accuracy in CD diagnosis and in molecular-based stratification of the patients, further reinforcing the functional involvement of the regulation of the autophagy

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

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    Peng, Zhaohua PEng [Mississippi State University; Ronald, Palmela [UC-Davis; Wang, Guo-Liang [The Ohio State University

    2013-04-26

    This project aims to identify the regulatory genes of rice cell wall synthesis pathways using a cell wall removal and regeneration system. We completed the gene expression profiling studies following the time course from cell wall removal to cell wall regeneration in rice suspension cells. We also completed, total proteome, nuclear subproteome and histone modification studies following the course from cell wall removal and cell wall regeneration process. A large number of differentially expressed regulatory genes and proteins were identified. Meanwhile, we generated RNAi and over-expression transgenic rice for 45 genes with at least 10 independent transgenic lines for each gene. In addition, we ordered T-DNA and transposon insertion mutants for 60 genes from Korea, Japan, and France and characterized the mutants. Overall, we have mutants and transgenic lines for over 90 genes, exceeded our proposed goal of generating mutants for 50 genes. Interesting Discoveries a) Cell wall re-synthesis in protoplasts may involve a novel cell wall synthesis mechanism. The synthesis of the primary cell wall is initiated in late cytokinesis with further modification during cell expansion. Phragmoplast plays an essential role in cell wall synthesis. It services as a scaffold for building the cell plate and formation of a new cell wall. Only one phragmoplast and one new cell wall is produced for each dividing cell. When the cell wall was removed enzymatically, we found that cell wall re-synthesis started from multiple locations simultaneously, suggesting that a novel mechanism is involved in cell wall re-synthesis. This observation raised many interesting questions, such as how the starting sites of cell wall synthesis are determined, whether phragmoplast and cell plate like structures are involved in cell wall re-synthesis, and more importantly whether the same set of enzymes and apparatus are used in cell wall re-synthesis as during cytokinesis. Given that many known cell wall

  11. Extensive evolutionary changes in regulatory element activity during human origins are associated with altered gene expression and positive selection.

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    Yoichiro Shibata

    2012-06-01

    Full Text Available Understanding the molecular basis for phenotypic differences between humans and other primates remains an outstanding challenge. Mutations in non-coding regulatory DNA that alter gene expression have been hypothesized as a key driver of these phenotypic differences. This has been supported by differential gene expression analyses in general, but not by the identification of specific regulatory elements responsible for changes in transcription and phenotype. To identify the genetic source of regulatory differences, we mapped DNaseI hypersensitive (DHS sites, which mark all types of active gene regulatory elements, genome-wide in the same cell type isolated from human, chimpanzee, and macaque. Most DHS sites were conserved among all three species, as expected based on their central role in regulating transcription. However, we found evidence that several hundred DHS sites were gained or lost on the lineages leading to modern human and chimpanzee. Species-specific DHS site gains are enriched near differentially expressed genes, are positively correlated with increased transcription, show evidence of branch-specific positive selection, and overlap with active chromatin marks. Species-specific sequence differences in transcription factor motifs found within these DHS sites are linked with species-specific changes in chromatin accessibility. Together, these indicate that the regulatory elements identified here are genetic contributors to transcriptional and phenotypic differences among primate species.

  12. Identification of genes for small non-coding RNAs that belong to the regulon of the two-component regulatory system CiaRH in Streptococcus

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    Hakenbeck Regine

    2010-11-01

    Full Text Available Abstract Background Post-transcriptional regulation by small RNAs (sRNAs in bacteria is now recognized as a wide-spread regulatory mechanism modulating a variety of physiological responses including virulence. In Streptococcus pneumoniae, an important human pathogen, the first sRNAs to be described were found in the regulon of the CiaRH two-component regulatory system. Five of these sRNAs were detected and designated csRNAs for cia-dependent small RNAs. CiaRH pleiotropically affects β-lactam resistance, autolysis, virulence, and competence development by yet to be defined molecular mechanisms. Since CiaRH is highly conserved among streptococci, it is of interest to determine if csRNAs are also included in the CiaRH regulon in this group of organisms consisting of commensal as well as pathogenic species. Knowledge on the participation of csRNAs in CiaRH-dependent regulatory events will be the key to define the physiological role of this important control system. Results Genes for csRNAs were predicted in streptococcal genomes and data base entries other than S. pneumoniae by searching for CiaR-activated promoters located in intergenic regions that are followed by a transcriptional terminator. 61 different candidate genes were obtained specifying csRNAs ranging in size from 51 to 202 nt. Comparing these genes among each other revealed 40 different csRNA types. All streptococcal genomes harbored csRNA genes, their numbers varying between two and six. To validate these predictions, S. mitis, S. oralis, and S. sanguinis were subjected to csRNA-specific northern blot analysis. In addition, a csRNA gene from S. thermophilus plasmid pST0 introduced into S. pneumoniae was also tested. Each of the csRNAs was detected on these blots and showed the anticipated sizes. Thus, the method applied here is able to predict csRNAs with high precision. Conclusions The results of this study strongly suggest that genes for small non-coding RNAs, csRNAs, are part of

  13. Gene regulatory networks in lactation: identification of global principles using bioinformatics

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    Pollard Katherine S

    2007-11-01

    Full Text Available Abstract Background The molecular events underlying mammary development during pregnancy, lactation, and involution are incompletely understood. Results Mammary gland microarray data, cellular localization data, protein-protein interactions, and literature-mined genes were integrated and analyzed using statistics, principal component analysis, gene ontology analysis, pathway analysis, and network analysis to identify global biological principles that govern molecular events during pregnancy, lactation, and involution. Conclusion Several key principles were derived: (1 nearly a third of the transcriptome fluctuates to build, run, and disassemble the lactation apparatus; (2 genes encoding the secretory machinery are transcribed prior to lactation; (3 the diversity of the endogenous portion of the milk proteome is derived from fewer than 100 transcripts; (4 while some genes are differentially transcribed near the onset of lactation, the lactation switch is primarily post-transcriptionally mediated; (5 the secretion of materials during lactation occurs not by up-regulation of novel genomic functions, but by widespread transcriptional suppression of functions such as protein degradation and cell-environment communication; (6 the involution switch is primarily transcriptionally mediated; and (7 during early involution, the transcriptional state is partially reverted to the pre-lactation state. A new hypothesis for secretory diminution is suggested – milk production gradually declines because the secretory machinery is not transcriptionally replenished. A comprehensive network of protein interactions during lactation is assembled and new regulatory gene targets are identified. Less than one fifth of the transcriptionally regulated nodes in this lactation network have been previously explored in the context of lactation. Implications for future research in mammary and cancer biology are discussed.

  14. Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

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    Lu, Tao

    2016-01-01

    The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

  15. DNA Methylation of Regulatory Regions of Imprinted Genes at Birth and Its Relation to Infant Temperament

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    Bernard F. Fuemmeler

    2016-01-01

    Full Text Available BACKGROUND DNA methylation of the differentially methylated regions (DMRs of imprinted genes is relevant to neurodevelopment. METHODS DNA methylation status of the DMRs of nine imprinted genes in umbilical cord blood leukocytes was analyzed in relation to infant behaviors and temperament (n = 158. RESULTS MEG3 DMR levels were positively associated with internalizing ( β = 0.15, P = 0.044 and surgency ( β = 0.19, P = 0.018 behaviors, after adjusting for birth weight, gender, gestational age at birth, maternal age at delivery, race/ethnicity, education level, smoking status, parity, and a history of anxiety or depression. Higher methylation levels at the intergenic MEG3-IG methylation regions were associated with surgency ( β = 0.28, P = 0.0003 and PEG3 was positively related to externalizing ( β = 0.20, P = 0.01 and negative affectivity ( β = 0.18, P = 0.02. CONCLUSION While the small sample size limits inference, these pilot data support gene-specific associations between epigenetic differences in regulatory regions of imprinted domains at birth and later infant temperament.

  16. Inference of time-delayed gene regulatory networks based on dynamic Bayesian network hybrid learning method.

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    Yu, Bin; Xu, Jia-Meng; Li, Shan; Chen, Cheng; Chen, Rui-Xin; Wang, Lei; Zhang, Yan; Wang, Ming-Hui

    2017-10-06

    Gene regulatory networks (GRNs) research reveals complex life phenomena from the perspective of gene interaction, which is an important research field in systems biology. Traditional Bayesian networks have a high computational complexity, and the network structure scoring model has a single feature. Information-based approaches cannot identify the direction of regulation. In order to make up for the shortcomings of the above methods, this paper presents a novel hybrid learning method (DBNCS) based on dynamic Bayesian network (DBN) to construct the multiple time-delayed GRNs for the first time, combining the comprehensive score (CS) with the DBN model. DBNCS algorithm first uses CMI2NI (conditional mutual inclusive information-based network inference) algorithm for network structure profiles learning, namely the construction of search space. Then the redundant regulations are removed by using the recursive optimization algorithm (RO), thereby reduce the false positive rate. Secondly, the network structure profiles are decomposed into a set of cliques without loss, which can significantly reduce the computational complexity. Finally, DBN model is used to identify the direction of gene regulation within the cliques and search for the optimal network structure. The performance of DBNCS algorithm is evaluated by the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in Escherichia coli , and compared with other state-of-the-art methods. The experimental results show the rationality of the algorithm design and the outstanding performance of the GRNs.

  17. Recurrent neural network-based modeling of gene regulatory network using elephant swarm water search algorithm.

    Science.gov (United States)

    Mandal, Sudip; Saha, Goutam; Pal, Rajat Kumar

    2017-08-01

    Correct inference of genetic regulations inside a cell from the biological database like time series microarray data is one of the greatest challenges in post genomic era for biologists and researchers. Recurrent Neural Network (RNN) is one of the most popular and simple approach to model the dynamics as well as to infer correct dependencies among genes. Inspired by the behavior of social elephants, we propose a new metaheuristic namely Elephant Swarm Water Search Algorithm (ESWSA) to infer Gene Regulatory Network (GRN). This algorithm is mainly based on the water search strategy of intelligent and social elephants during drought, utilizing the different types of communication techniques. Initially, the algorithm is tested against benchmark small and medium scale artificial genetic networks without and with presence of different noise levels and the efficiency was observed in term of parametric error, minimum fitness value, execution time, accuracy of prediction of true regulation, etc. Next, the proposed algorithm is tested against the real time gene expression data of Escherichia Coli SOS Network and results were also compared with others state of the art optimization methods. The experimental results suggest that ESWSA is very efficient for GRN inference problem and performs better than other methods in many ways.

  18. HAND2 Target Gene Regulatory Networks Control Atrioventricular Canal and Cardiac Valve Development.

    Science.gov (United States)

    Laurent, Frédéric; Girdziusaite, Ausra; Gamart, Julie; Barozzi, Iros; Osterwalder, Marco; Akiyama, Jennifer A; Lincoln, Joy; Lopez-Rios, Javier; Visel, Axel; Zuniga, Aimée; Zeller, Rolf

    2017-05-23

    The HAND2 transcriptional regulator controls cardiac development, and we uncover additional essential functions in the endothelial to mesenchymal transition (EMT) underlying cardiac cushion development in the atrioventricular canal (AVC). In Hand2-deficient mouse embryos, the EMT underlying AVC cardiac cushion formation is disrupted, and we combined ChIP-seq of embryonic hearts with transcriptome analysis of wild-type and mutants AVCs to identify the functionally relevant HAND2 target genes. The HAND2 target gene regulatory network (GRN) includes most genes with known functions in EMT processes and AVC cardiac cushion formation. One of these is Snai1, an EMT master regulator whose expression is lost from Hand2-deficient AVCs. Re-expression of Snai1 in mutant AVC explants partially restores this EMT and mesenchymal cell migration. Furthermore, the HAND2-interacting enhancers in the Snai1 genomic landscape are active in embryonic hearts and other Snai1-expressing tissues. These results show that HAND2 directly regulates the molecular cascades initiating AVC cardiac valve development. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  19. Comparative metabolomics in primates reveals the effects of diet and gene regulatory variation on metabolic divergence.

    Science.gov (United States)

    Blekhman, Ran; Perry, George H; Shahbaz, Sevini; Fiehn, Oliver; Clark, Andrew G; Gilad, Yoav

    2014-07-28

    Human diets differ from those of non-human primates. Among few obvious differences, humans consume more meat than most non-human primates and regularly cook their food. It is hypothesized that a dietary shift during human evolution has been accompanied by molecular adaptations in metabolic pathways. Consistent with this notion, comparative studies of gene expression levels in primates have found that the regulation of genes with metabolic functions tend to evolve rapidly in the human lineage. The metabolic consequences of these regulatory differences, however, remained unknown. To address this gap, we performed a comparative study using a combination of gene expression and metabolomic profiling in livers from humans, chimpanzees, and rhesus macaques. We show that dietary differences between species have a strong effect on metabolic concentrations. In addition, we found that differences in metabolic concentration across species are correlated with inter-species differences in the expression of the corresponding enzymes, which control the same metabolic reaction. We identified a number of metabolic compounds with lineage-specific profiles, including examples of human-species metabolic differences that may be directly related to dietary differences.

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

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    Santra, Tapesh, E-mail: tapesh.santra@ucd.ie [Systems Biology Ireland, University College Dublin, Dublin (Ireland)

    2014-05-20

    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.

  1. Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

    Science.gov (United States)

    Patel, Nihir; Wang, Jason T L

    2015-10-01

    Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

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

    International Nuclear Information System (INIS)

    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.

  3. Genetic Variation of Goat Interferon Regulatory Factor 3 Gene and Its Implication in Goat Evolution.

    Science.gov (United States)

    Okpeku, Moses; Esmailizadeh, Ali; Adeola, Adeniyi C; Shu, Liping; Zhang, Yesheng; Wang, Yangzi; Sanni, Timothy M; Imumorin, Ikhide G; Peters, Sunday O; Zhang, Jiajin; Dong, Yang; Wang, Wen

    2016-01-01

    The immune systems are fundamentally vital for evolution and survival of species; as such, selection patterns in innate immune loci are of special interest in molecular evolutionary research. The interferon regulatory factor (IRF) gene family control many different aspects of the innate and adaptive immune responses in vertebrates. Among these, IRF3 is known to take active part in very many biological processes. We assembled and evaluated 1356 base pairs of the IRF3 gene coding region in domesticated goats from Africa (Nigeria, Ethiopia and South Africa) and Asia (Iran and China) and the wild goat (Capra aegagrus). Five segregating sites with θ value of 0.0009 for this gene demonstrated a low diversity across the goats' populations. Fu and Li tests were significantly positive but Tajima's D test was significantly negative, suggesting its deviation from neutrality. Neighbor joining tree of IRF3 gene in domesticated goats, wild goat and sheep showed that all domesticated goats have a closer relationship than with the wild goat and sheep. Maximum likelihood tree of the gene showed that different domesticated goats share a common ancestor and suggest single origin. Four unique haplotypes were observed across all the sequences, of which, one was particularly common to African goats (MOCH-K14-0425, Poitou and WAD). In assessing the evolution mode of the gene, we found that the codon model dN/dS ratio for all goats was greater than one. Phylogenetic Analysis by Maximum Likelihood (PAML) gave a ω0 (dN/dS) value of 0.067 with LnL value of -6900.3 for the first Model (M1) while ω2 = 1.667 in model M2 with LnL value of -6900.3 with positive selection inferred in 3 codon sites. Mechanistic empirical combination (MEC) model for evaluating adaptive selection pressure on particular codons also confirmed adaptive selection pressure in three codons (207, 358 and 408) in IRF3 gene. Positive diversifying selection inferred with recent evolutionary changes in domesticated goat IRF3

  4. Sub-circuits of a gene regulatory network control a developmental epithelial-mesenchymal transition.

    Science.gov (United States)

    Saunders, Lindsay R; McClay, David R

    2014-04-01

    Epithelial-mesenchymal transition (EMT) is a fundamental cell state change that transforms epithelial to mesenchymal cells during embryonic development, adult tissue repair and cancer metastasis. EMT includes a complex series of intermediate cell state changes including remodeling of the basement membrane, apical constriction, epithelial de-adhesion, directed motility, loss of apical-basal polarity, and acquisition of mesenchymal adhesion and polarity. Transcriptional regulatory state changes must ultimately coordinate the timing and execution of these cell biological processes. A well-characterized gene regulatory network (GRN) in the sea urchin embryo was used to identify the transcription factors that control five distinct cell changes during EMT. Single transcription factors were perturbed and the consequences followed with in vivo time-lapse imaging or immunostaining assays. The data show that five different sub-circuits of the GRN control five distinct cell biological activities, each part of the complex EMT process. Thirteen transcription factors (TFs) expressed specifically in pre-EMT cells were required for EMT. Three TFs highest in the GRN specified and activated EMT (alx1, ets1, tbr) and the 10 TFs downstream of those (tel, erg, hex, tgif, snail, twist, foxn2/3, dri, foxb, foxo) were also required for EMT. No single TF functioned in all five sub-circuits, indicating that there is no EMT master regulator. Instead, the resulting sub-circuit topologies suggest EMT requires multiple simultaneous regulatory mechanisms: forward cascades, parallel inputs and positive-feedback lock downs. The interconnected and overlapping nature of the sub-circuits provides one explanation for the seamless orchestration by the embryo of cell state changes leading to successful EMT.

  5. A novel proapoptotic gene PANO encodes a post-translational modulator of the tumor suppressor p14ARF

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    Watari, Akihiro; Li, Yang; Higashiyama, Shinji; Yutsudo, Masuo, E-mail: yutsudo@biken.osaka-u.ac.jp

    2012-02-01

    The protein p14ARF is a known tumor suppressor protein controlling cell proliferation and survival, which mainly localizes in nucleoli. However, the regulatory mechanisms that govern its activity or expression remain unclear. Here, we report that a novel proapoptotic nucleolar protein, PANO, modulates the expression and activity of p14ARF in HeLa cells. Overexpression of PANO enhances the stability of p14ARF protein by protecting it from degradation, resulting in an increase in p14ARF expression levels. Overexpression of PANO also induces apoptosis under low serum conditions. This effect is dependent on the nucleolar localization of PANO and inhibited by knocking-down p14ARF. Alternatively, PANO siRNA treated cells exhibit a reduction in p14ARF protein levels. In addition, ectopic expression of PANO suppresses the tumorigenicity of HeLa cells in nude mice. These results indicate that PANO is a new apoptosis-inducing gene by modulating the tumor suppressor protein, p14ARF, and may itself be a new candidate tumor suppressor gene.

  6. Highly preserved consensus gene modules in human papilloma virus 16 positive cervical cancer and head and neck cancers.

    Science.gov (United States)

    Zhang, Xianglan; Cha, In-Ho; Kim, Ki-Yeol

    2017-12-26

    In this study, we investigated the consensus gene modules in head and neck cancer (HNC) and cervical cancer (CC). We used a publicly available gene expression dataset, GSE6791, which included 42 HNC, 14 normal head and neck, 20 CC and 8 normal cervical tissue samples. To exclude bias because of different human papilloma virus (HPV) types, we analyzed HPV16-positive samples only. We identified 3824 genes common to HNC and CC samples. Among these, 977 genes showed high connectivity and were used to construct consensus modules. We demonstrated eight consensus gene modules for HNC and CC using the dissimilarity measure and average linkage hierarchical clustering methods. These consensus modules included genes with significant biological functions, including ATP binding and extracellular exosome. Eigengen network analysis revealed the consensus modules were highly preserved with high connectivity. These findings demonstrate that HPV16-positive head and neck and cervical cancers share highly preserved consensus gene modules with common potentially therapeutic targets.

  7. Conserved regulatory modules in the Sox9 testis-specific enhancer predict roles for SOX, TCF/LEF, Forkhead, DMRT, and GATA proteins in vertebrate sex determination.

    Science.gov (United States)

    Bagheri-Fam, Stefan; Sinclair, Andrew H; Koopman, Peter; Harley, Vincent R

    2010-03-01

    While the primary sex determining switch varies between vertebrate species, a key downstream event in testicular development, namely the male-specific up-regulation of Sox9, is conserved. To date, only two sex determining switch genes have been identified, Sry in mammals and the Dmrt1-related gene Dmy (Dmrt1bY) in the medaka fish Oryzias latipes. In mice, Sox9 expression is evidently up-regulated by SRY and maintained by SOX9 both of which directly activate the core 1.3 kb testis-specific enhancer of Sox9 (TESCO). How Sox9 expression is up-regulated and maintained in species without Sry (i.e. non-mammalian species) is not understood. In this study, we have undertaken an in-depth comparative genomics approach and show that TESCO contains an evolutionarily conserved region (ECR) of 180 bp which is present in marsupials, monotremes, birds, reptiles and amphibians. The ECR contains highly conserved modules that predict regulatory roles for SOX, TCF/LEF, Forkhead, DMRT, and GATA proteins in vertebrate sex determination/differentiation. Our data suggest that tetrapods share common aspects of Sox9 regulation in the testis, despite having different sex determining switch mechanisms. They also suggest that Sox9 autoregulation is an ancient mechanism shared by all tetrapods, raising the possibility that in mammals, SRY evolved by mimicking this regulation. The validation of ECR regulatory sequences conserved from human to frogs will provide new insights into vertebrate sex determination. Copyright 2009 Elsevier Ltd. All rights reserved.

  8. SLAM-seq defines direct gene-regulatory functions of the BRD4-MYC axis.

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    Muhar, Matthias; Ebert, Anja; Neumann, Tobias; Umkehrer, Christian; Jude, Julian; Wieshofer, Corinna; Rescheneder, Philipp; Lipp, Jesse J; Herzog, Veronika A; Reichholf, Brian; Cisneros, David A; Hoffmann, Thomas; Schlapansky, Moritz F; Bhat, Pooja; von Haeseler, Arndt; Köcher, Thomas; Obenauf, Anna C; Popow, Johannes; Ameres, Stefan L; Zuber, Johannes

    2018-05-18

    Defining direct targets of transcription factors and regulatory pathways is key to understanding their roles in physiology and disease. We combined SLAM-seq [thiol(SH)-linked alkylation for the metabolic sequencing of RNA], a method for direct quantification of newly synthesized messenger RNAs (mRNAs), with pharmacological and chemical-genetic perturbation in order to define regulatory functions of two transcriptional hubs in cancer, BRD4 and MYC, and to interrogate direct responses to BET bromodomain inhibitors (BETis). We found that BRD4 acts as general coactivator of RNA polymerase II-dependent transcription, which is broadly repressed upon high-dose BETi treatment. At doses triggering selective effects in leukemia, BETis deregulate a small set of hypersensitive targets including MYC. In contrast to BRD4, MYC primarily acts as a selective transcriptional activator controlling metabolic processes such as ribosome biogenesis and de novo purine synthesis. Our study establishes a simple and scalable strategy to identify direct transcriptional targets of any gene or pathway. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  9. Mustn1: A Developmentally Regulated Pan-Musculoskeletal Cell Marker and Regulatory Gene

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    Michael Hadjiargyrou

    2018-01-01

    Full Text Available The Mustn1 gene encodes a small nuclear protein (~9.6 kDa that does not belong to any known family. Its genomic organization consists of three exons interspersed by two introns and it is highly homologous across vertebrate species. Promoter analyses revealed that its expression is regulated by the AP family of transcription factors, especially c-Fos, Fra-2 and JunD. Mustn1 is predominantly expressed in the major tissues of the musculoskeletal system: bone, cartilage, skeletal muscle and tendon. Its expression has been associated with normal embryonic development, postnatal growth, exercise, and regeneration of bone and skeletal muscle. Moreover, its expression has also been detected in various musculoskeletal pathologies, including arthritis, Duchenne muscular dystrophy, other skeletal muscle myopathies, clubfoot and diabetes associated muscle pathology. In vitro and in vivo functional perturbation revealed that Mustn1 is a key regulatory molecule in myogenic and chondrogenic lineages. This comprehensive review summarizes our current knowledge of Mustn1 and proposes that it is a new developmentally regulated pan-musculoskeletal marker as well as a key regulatory protein for cell differentiation and tissue growth.

  10. Localizing potentially active post-transcriptional regulations in the Ewing's sarcoma gene regulatory network

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    Delyon Bernard

    2010-11-01

    Full Text Available Abstract Background A wide range of techniques is now available for analyzing regulatory networks. Nonetheless, most of these techniques fail to interpret large-scale transcriptional data at the post-translational level. Results We address the question of using large-scale transcriptomic observation of a system perturbation to analyze a regulatory network which contained several types of interactions - transcriptional and post-translational. Our method consisted of post-processing the outputs of an open-source tool named BioQuali - an automatic constraint-based analysis mimicking biologist's local reasoning on a large scale. The post-processing relied on differences in the behavior of the transcriptional and post-translational levels in the network. As a case study, we analyzed a network representation of the genes and proteins controlled by an oncogene in the context of Ewing's sarcoma. The analysis allowed us to pinpoint active interactions specific to this cancer. We also identified the parts of the network which were incomplete and should be submitted for further investigation. Conclusions The proposed approach is effective for the qualitative analysis of cancer networks. It allows the integrative use of experimental data of various types in order to identify the specific information that should be considered a priority in the initial - and possibly very large - experimental dataset. Iteratively, new dataset can be introduced into the analysis to improve the network representation and make it more specific.

  11. Morphogenesis in sea urchin embryos: linking cellular events to gene regulatory network states

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    Lyons, Deidre; Kaltenbach, Stacy; McClay, David R.

    2013-01-01

    Gastrulation in the sea urchin begins with ingression of the primary mesenchyme cells (PMCs) at the vegetal pole of the embryo. After entering the blastocoel the PMCs migrate, form a syncitium, and synthesize the skeleton of the embryo. Several hours after the PMCs ingress the vegetal plate buckles to initiate invagination of the archenteron. That morphogenetic process occurs in several steps. The non-skeletogenic cells produce the initial inbending of the vegetal plate. Endoderm cells then rearrange and extend the length of the gut across the blastocoel to a target near the animal pole. Finally, cells that will form part of the midgut and hindgut are added to complete gastrulation. Later, the stomodeum invaginates from the oral ectoderm and fuses with the foregut to complete the archenteron. In advance of, and during these morphogenetic events an increasingly complex gene regulatory network controls the specification and the cell biological events that conduct the gastrulation movements. PMID:23801438

  12. NetBenchmark: a bioconductor package for reproducible benchmarks of gene regulatory network inference.

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    Bellot, Pau; Olsen, Catharina; Salembier, Philippe; Oliveras-Vergés, Albert; Meyer, Patrick E

    2015-09-29

    In the last decade, a great number of methods for reconstructing gene regulatory networks from expression data have been proposed. However, very few tools and datasets allow to evaluate accurately and reproducibly those methods. Hence, we propose here a new tool, able to perform a systematic, yet fully reproducible, evaluation of transcriptional network inference methods. Our open-source and freely available Bioconductor package aggregates a large set of tools to assess the robustness of network inference algorithms against different simulators, topologies, sample sizes and noise intensities. The benchmarking framework that uses various datasets highlights the specialization of some methods toward network types and data. As a result, it is possible to identify the techniques that have broad overall performances.

  13. Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

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    Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand

    2015-05-01

    Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.

  14. Model checking optimal finite-horizon control for probabilistic gene regulatory networks.

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    Wei, Ou; Guo, Zonghao; Niu, Yun; Liao, Wenyuan

    2017-12-14

    Probabilistic Boolean networks (PBNs) have been proposed for analyzing external control in gene regulatory networks with incorporation of uncertainty. A context-sensitive PBN with perturbation (CS-PBNp), extending a PBN with context-sensitivity to reflect the inherent biological stability and random perturbations to express the impact of external stimuli, is considered to be more suitable for modeling small biological systems intervened by conditions from the outside. In this paper, we apply probabilistic model checking, a formal verification technique, to optimal control for a CS-PBNp that minimizes the expected cost over a finite control horizon. We first describe a procedure of modeling a CS-PBNp using the language provided by a widely used probabilistic model checker PRISM. We then analyze the reward-based temporal properties and the computation in probabilistic model checking; based on the analysis, we provide a method to formulate the optimal control problem as minimum reachability reward properties. Furthermore, we incorporate control and state cost information into the PRISM code of a CS-PBNp such that automated model checking a minimum reachability reward property on the code gives the solution to the optimal control problem. We conduct experiments on two examples, an apoptosis network and a WNT5A network. Preliminary experiment results show the feasibility and effectiveness of our approach. The approach based on probabilistic model checking for optimal control avoids explicit computation of large-size state transition relations associated with PBNs. It enables a natural depiction of the dynamics of gene regulatory networks, and provides a canonical form to formulate optimal control problems using temporal properties that can be automated solved by leveraging the analysis power of underlying model checking engines. This work will be helpful for further utilization of the advances in formal verification techniques in system biology.

  15. Interferon regulatory factor 5 gene polymorphism in Egyptian children with systemic lupus erythematosus.

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    Hammad, A; Mossad, Y M; Nasef, N; Eid, R

    2017-07-01

    Background Increased expression of interferon-inducible genes is implicated in the pathogenesis of systemic lupus erythematosus (SLE). Interferon regulatory factor 5 (IRF5) is one of the transcription factors regulating interferon and was proved to be implicated in the pathogenesis of SLE in different populations. Objectives The objective of this study was to investigate the correlation between polymorphisms of the IRF5 gene and SLE susceptibility in a cohort of Egyptian children and to investigate their association with clinico-pathological features, especially lupus nephritis. Subjects and methods Typing of interferon regulatory factor 5 rs10954213, rs2004640 and rs2280714 polymorphisms were done using polymerase chain reaction-restriction fragment length polymorphism for 100 children with SLE and 100 matched healthy controls. Results Children with SLE had more frequent T allele and TT genotype of rs2004640 ( P c  = 0.003 and 0.024, respectively) compared to controls. Patients with nephritis had more frequent T allele of rs2004640 compared to controls ( P c  = 0.003). However the allele and genotype frequencies of the three studied polymorphisms did not show any difference in patients with nephritis in comparison to those without nephritis. Haplotype GTA of rs10954213, rs2004640 and rs2280714, respectively, was more frequent in lupus patients in comparison to controls ( p = 0.01) while the haplotype GGG was more frequent in controls than lupus patients ( p = 0.011). Conclusion The rs2004640 T allele and TT genotype and GTA haplotype of rs rs10954213, rs2004640, and rs2280714, respectively, can be considered as risk factors for the development of SLE. The presence of the rs2004640 T allele increases the risk of nephritis development in Egyptian children with SLE.

  16. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study.

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    Alexandra C Nica

    2011-02-01

    Full Text Available While there have been studies exploring regulatory variation in one or more tissues, the complexity of tissue-specificity in multiple primary tissues is not yet well understood. We explore in depth the role of cis-regulatory variation in three human tissues: lymphoblastoid cell lines (LCL, skin, and fat. The samples (156 LCL, 160 skin, 166 fat were derived simultaneously from a subset of well-phenotyped healthy female twins of the MuTHER resource. We discover an abundance of cis-eQTLs in each tissue similar to previous estimates (858 or 4.7% of genes. In addition, we apply factor analysis (FA to remove effects of latent variables, thus more than doubling the number of our discoveries (1,822 eQTL genes. The unique study design (Matched Co-Twin Analysis--MCTA permits immediate replication of eQTLs using co-twins (93%-98% and validation of the considerable gain in eQTL discovery after FA correction. We highlight the challenges of comparing eQTLs between tissues. After verifying previous significance threshold-based estimates of tissue-specificity, we show their limitations given their dependency on statistical power. We propose that continuous estimates of the proportion of tissue-shared signals and direct comparison of the magnitude of effect on the fold change in expression are essential properties that jointly provide a biologically realistic view of tissue-specificity. Under this framework we demonstrate that 30% of eQTLs are shared among the three tissues studied, while another 29% appear exclusively tissue-specific. However, even among the shared eQTLs, a substantial proportion (10%-20% have significant differences in the magnitude of fold change between genotypic classes across tissues. Our results underline the need to account for the complexity of eQTL tissue-specificity in an effort to assess consequences of such variants for complex traits.

  17. The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes

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    Xinguo Lu

    2018-01-01

    Full Text Available With advances in next-generation sequencing(NGS technologies, a large number of multiple types of high-throughput genomics data are available. A great challenge in exploring cancer progression is to identify the driver genes from the variant genes by analyzing and integrating multi-types genomics data. Breast cancer is known as a heterogeneous disease. The identification of subtype-specific driver genes is critical to guide the diagnosis, assessment of prognosis and treatment of breast cancer. We developed an integrated frame based on gene expression profiles and copy number variation (CNV data to identify breast cancer subtype-specific driver genes. In this frame, we employed statistical machine-learning method to select gene subsets and utilized an module-network analysis method to identify potential candidate driver genes. The final subtype-specific driver genes were acquired by paired-wise comparison in subtypes. To validate specificity of the driver genes, the gene expression data of these genes were applied to classify the patient samples with 10-fold cross validation and the enrichment analysis were also conducted on the identified driver genes. The experimental results show that the proposed integrative method can identify the potential driver genes and the classifier with these genes acquired better performance than with genes identified by other methods.

  18. Drought Response in Wheat: Key Genes and Regulatory Mechanisms Controlling Root System Architecture and Transpiration Efficiency

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    Manoj Kulkarni

    2017-12-01

    gold-standard reference genome sequence and advent of genome editing technologies, are expected to aid in deciphering of the functional roles of genes and regulatory networks underlying adaptive phenological traits, and utilizing the outcomes of such studies in developing drought tolerant cultivars.

  19. Conservation of lipid metabolic gene transcriptional regulatory networks in fish and mammals.

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    Carmona-Antoñanzas, Greta; Tocher, Douglas R; Martinez-Rubio, Laura; Leaver, Michael J

    2014-01-15

    Lipid content and composition in aquafeeds have changed rapidly as a result of the recent drive to replace ecologically limited marine ingredients, fishmeal and fish oil (FO). Terrestrial plant products are the most economic and sustainable alternative; however, plant meals and oils are devoid of physiologically important cholesterol and long-chain polyunsaturated fatty acids (LC-PUFA), eicosapentaenoic (EPA), docosahexaenoic (DHA) and arachidonic (ARA) acids. Although replacement of dietary FO with vegetable oil (VO) has little effect on growth in Atlantic salmon (Salmo salar), several studies have shown major effects on the activity and expression of genes involved in lipid homeostasis. In vertebrates, sterols and LC-PUFA play crucial roles in lipid metabolism by direct interaction with lipid-sensing transcription factors (TFs) and consequent regulation of target genes. The primary aim of the present study was to elucidate the role of key TFs in the transcriptional regulation of lipid metabolism in fish by transfection and overexpression of TFs. The results show that the expression of genes of LC-PUFA biosynthesis (elovl and fads2) and cholesterol metabolism (abca1) are regulated by Lxr and Srebp TFs in salmon, indicating highly conserved regulatory mechanism across vertebrates. In addition, srebp1 and srebp2 mRNA respond to replacement of dietary FO with VO. Thus, Atlantic salmon adjust lipid metabolism in response to dietary lipid composition through the transcriptional regulation of gene expression. It may be possible to further increase efficient and effective use of sustainable alternatives to marine products in aquaculture by considering these important molecular interactions when formulating diets. © 2013.

  20. Human Sterol Regulatory Element-Binding Protein 1a Contributes Significantly to Hepatic Lipogenic Gene Expression

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    Andreas Bitter

    2015-01-01

    Full Text Available Background/Aims: Sterol regulatory element-binding protein (SREBP 1, the master regulator of lipogenesis, was shown to be associated with non-alcoholic fatty liver disease, which is attributed to its major isoform SREBP1c. Based on studies in mice, the minor isoform SREBP1a is regarded as negligible for hepatic lipogenesis. This study aims to elucidate the expression and functional role of SREBP1a in human liver. Methods: mRNA expression of both isoforms was quantified in cohorts of human livers and primary human hepatocytes. Hepatocytes were treated with PF-429242 to inhibit the proteolytic activation of SREBP precursor protein. SREBP1a-specifc and pan-SREBP1 knock-down were performed by transfection of respective siRNAs. Lipogenic SREBP-target gene expression was analyzed by real-time RT-PCR. Results: In human liver, SREBP1a accounts for up to half of the total SREBP1 pool. Treatment with PF-429242 indicated SREBP-dependent auto-regulation of SREBP1a, which however was much weaker than of SREBP1c. SREBP1a-specifc knock-down also reduced significantly the expression of SREBP1c and of SREBP-target genes. Regarding most SREBP-target genes, simultaneous knock-down of both isoforms resulted in effects of only similar extent as SREBP1a-specific knock-down. Conclusion: We here showed that SREBP1a is significantly contributing to the human hepatic SREBP1 pool and has a share in human hepatic lipogenic gene expression.

  1. ChIPBase v2.0: decoding transcriptional regulatory networks of non-coding RNAs and protein-coding genes from ChIP-seq data.

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    Zhou, Ke-Ren; Liu, Shun; Sun, Wen-Ju; Zheng, Ling-Ling; Zhou, Hui; Yang, Jian-Hua; Qu, Liang-Hu

    2017-01-04

    The abnormal transcriptional regulation of non-coding RNAs (ncRNAs) and protein-coding genes (PCGs) is contributed to various biological processes and linked with human diseases, but the underlying mechanisms remain elusive. In this study, we developed ChIPBase v2.0 (http://rna.sysu.edu.cn/chipbase/) to explore the transcriptional regulatory networks of ncRNAs and PCGs. ChIPBase v2.0 has been expanded with ∼10 200 curated ChIP-seq datasets, which represent about 20 times expansion when comparing to the previous released version. We identified thousands of binding motif matrices and their binding sites from ChIP-seq data of DNA-binding proteins and predicted millions of transcriptional regulatory relationships between transcription factors (TFs) and genes. We constructed 'Regulator' module to predict hundreds of TFs and histone modifications that were involved in or affected transcription of ncRNAs and PCGs. Moreover, we built a web-based tool, Co-Expression, to explore the co-expression patterns between DNA-binding proteins and various types of genes by integrating the gene expression profiles of ∼10 000 tumor samples and ∼9100 normal tissues and cell lines. ChIPBase also provides a ChIP-Function tool and a genome browser to predict functions of diverse genes and visualize various ChIP-seq data. This study will greatly expand our understanding of the transcriptional regulations of ncRNAs and PCGs. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Evolution of New cis-Regulatory Motifs Required for Cell-Specific Gene Expression in Caenorhabditis.

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    Michalis Barkoulas

    2016-09-01

    Full Text Available Patterning of C. elegans vulval cell fates relies on inductive signaling. In this induction event, a single cell, the gonadal anchor cell, secretes LIN-3/EGF and induces three out of six competent precursor cells to acquire a vulval fate. We previously showed that this developmental system is robust to a four-fold variation in lin-3/EGF genetic dose. Here using single-molecule FISH, we find that the mean level of expression of lin-3 in the anchor cell is remarkably conserved. No change in lin-3 expression level could be detected among C. elegans wild isolates and only a low level of change-less than 30%-in the Caenorhabditis genus and in Oscheius tipulae. In C. elegans, lin-3 expression in the anchor cell is known to require three transcription factor binding sites, specifically two E-boxes and a nuclear-hormone-receptor (NHR binding site. Mutation of any of these three elements in C. elegans results in a dramatic decrease in lin-3 expression. Yet only a single E-box is found in the Drosophilae supergroup of Caenorhabditis species, including C. angaria, while the NHR-binding site likely only evolved at the base of the Elegans group. We find that a transgene from C. angaria bearing a single E-box is sufficient for normal expression in C. elegans. Even a short 58 bp cis-regulatory fragment from C. angaria with this single E-box is able to replace the three transcription factor binding sites at the endogenous C. elegans lin-3 locus, resulting in the wild-type expression level. Thus, regulatory evolution occurring in cis within a 58 bp lin-3 fragment, results in a strict requirement for the NHR binding site and a second E-box in C. elegans. This single-cell, single-molecule, quantitative and functional evo-devo study demonstrates that conserved expression levels can hide extensive change in cis-regulatory site requirements and highlights the evolution of new cis-regulatory elements required for cell-specific gene expression.

  3. Importância de polimorfismos de genes reguladores de citocinas em transplantes de células progenitoras hematopoiéticas Importance of regulatory cytokine gene polymorphisms in hematopoietic stem cell transplantation

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    Jeane Eliete Laguila Visentainer

    2008-12-01

    Full Text Available A compatibilidade genética HLA entre doador e receptor é um fator importante para o sucesso do transplante de células progenitoras hematopoiéticas (TCPH. No entanto, outros genes não-HLA estão sendo investigados em relação ao seu papel na incidência e gravidade da doença do enxerto contra o hospedeiro e na sobrevida, por modularem a intensidade da inflamação e os danos teciduais. Estes genes, não-HLA, incluem os genes de citocinas com polimorfismos dentro das seqüências 5' ou 3' regulatórias dos genes. Os polimorfismos ou microssatélites podem alterar a ligação dos fatores de transcrição aos sítios dentro dos genes promotores e a quantidade de citocina produzida. Este estudo revisa o papel potencial destes polimorfismos genéticos relativos às citocinas em prever o curso do TCPH.HLA genetic matching of donor and recipient is an important requirement for optimizing outcome following hematopoietic stem cell transplantation (HSCT. However, other non-HLA genes are being investigated for their role in graft-versus-host disease incidence and severity and in survival, by modulating the intensity of inflammation and tissue injury. These non-HLA-encoded genes include cytokine genes with polymorphisms within the 5' or 3' regulatory sequences of the genes. The polymorphisms or microsatellites may alter the transcription factor binding sites within the gene promoters and the amount of cytokine produced. This chapter summarizes the potential role of these genetic polymorphisms regarding the cytokines in predicting outcome of HSCT.

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

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    Mars, Ruben A. T.; Nicolas, Pierre; Denham, Emma L.

    2016-01-01

    SUMMARY Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5′ untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5′ ends of mRNA molecules. These can include 5′ secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis. PMID:27784798

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

    Science.gov (United States)

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

    2016-12-01

    Bacteria can employ widely diverse RNA molecules to regulate their gene expression. Such molecules include trans-acting small regulatory RNAs, antisense RNAs, and a variety of transcriptional attenuation mechanisms in the 5' untranslated region. Thus far, most regulatory RNA research has focused on Gram-negative bacteria, such as Escherichia coli and Salmonella. Hence, there is uncertainty about whether the resulting insights can be extrapolated directly to other bacteria, such as the Gram-positive soil bacterium Bacillus subtilis. A recent study identified 1,583 putative regulatory RNAs in B. subtilis, whose expression was assessed across 104 conditions. Here, we review the current understanding of RNA-based regulation in B. subtilis, and we categorize the newly identified putative regulatory RNAs on the basis of their conservation in other bacilli and the stability of their predicted secondary structures. Our present evaluation of the publicly available data indicates that RNA-mediated gene regulation in B. subtilis mostly involves elements at the 5' ends of mRNA molecules. These can include 5' secondary structure elements and metabolite-, tRNA-, or protein-binding sites. Importantly, sense-independent segments are identified as the most conserved and structured potential regulatory RNAs in B. subtilis. Altogether, the present survey provides many leads for the identification of new regulatory RNA functions in B. subtilis. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

  6. Predictability of Genetic Interactions from Functional Gene Modules

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    Jonathan H. Young

    2017-02-01

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

  7. A systems biology approach to construct the gene regulatory network of systemic inflammation via microarray and databases mining

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    Lan Chung-Yu

    2008-09-01

    Full Text Available Abstract Background Inflammation is a hallmark of many human diseases. Elucidating the mechanisms underlying systemic inflammation has long been an important topic in basic and clinical research. When primary pathogenetic events remains unclear due to its immense complexity, construction and analysis of the gene regulatory network of inflammation at times becomes the best way to understand the detrimental effects of disease. However, it is difficult to recognize and evaluate relevant biological processes from the huge quantities of experimental data. It is hence appealing to find an algorithm which can generate a gene regulatory network of systemic inflammation from high-throughput genomic studies of human diseases. Such network will be essential for us to extract valuable information from the complex and chaotic network under diseased conditions. Results In this study, we construct a gene regulatory network of inflammation using data extracted from the Ensembl and JASPAR databases. We also integrate and apply a number of systematic algorithms like cross correlation threshold, maximum likelihood estimation method and Akaike Information Criterion (AIC on time-lapsed microarray data to refine the genome-wide transcriptional regulatory network in response to bacterial endotoxins in the context of dynamic activated genes, which are regulated by transcription factors (TFs such as NF-κB. This systematic approach is used to investigate the stochastic interaction represented by the dynamic leukocyte gene expression profiles of human subject exposed to an inflammatory stimulus (bacterial endotoxin. Based on the kinetic parameters of the dynamic gene regulatory network, we identify important properties (such as susceptibility to infection of the immune system, which may be useful for translational research. Finally, robustness of the inflammatory gene network is also inferred by analyzing the hubs and "weak ties" structures of the gene network

  8. Sterol regulatory element binding protein-1 (SREBP1) gene expression is similarly increased in polycystic ovary syndrome and endometrial cancer.

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    Shafiee, Mohamad N; Mongan, Nigel; Seedhouse, Claire; Chapman, Caroline; Deen, Suha; Abu, Jafaru; Atiomo, William

    2017-05-01

    Women with polycystic ovary syndrome have a three-fold higher risk of endometrial cancer. Insulin resistance and hyperlipidemia may be pertinent factors in the pathogenesis of both conditions. The aim of this study was to investigate endometrial sterol regulatory element binding protein-1 gene expression in polycystic ovary syndrome and endometrial cancer endometrium, and to correlate endometrial sterol regulatory element binding protein-1 gene expression with serum lipid profiles. A cross-sectional study was performed at Nottingham University Hospital, UK. A total of 102 women (polycystic ovary syndrome, endometrial cancer and controls; 34 participants in each group) were recruited. Clinical and biochemical assessments were performed before endometrial biopsies were obtained from all participants. Taqman real-time polymerase chain reaction for endometrial sterol regulatory element binding protein-1 gene and its systemic protein expression were analyzed. The body mass indices of women with polycystic ovary syndrome (29.28 ± 2.91 kg/m 2 ) and controls (28.58 ± 2.62 kg/m 2 ) were not significantly different. Women with endometrial cancer had a higher mean body mass index (32.22 ± 5.70 kg/m 2 ). Sterol regulatory element binding protein-1 gene expression was significantly increased in polycystic ovary syndrome and endometrial cancer endometrium compared with controls (p ovary syndrome, but this was not statistically significant. Similarly, statistically insignificant positive correlations were found between endometrial sterol regulatory element binding protein-1 gene expression and body mass index in endometrial cancer (r = 0.643, p = 0.06) and waist-hip ratio (r = 0.096, p = 0.073). Sterol regulatory element binding protein-1 gene expression was significantly positively correlated with triglyceride in both polycystic ovary syndrome and endometrial cancer (p = 0.028 and p = 0.027, respectively). Quantitative serum sterol regulatory element

  9. Distinct gene regulatory programs define the inhibitory effects of liver X receptors and PPARG on cancer cell proliferation.

    Science.gov (United States)

    Savic, Daniel; Ramaker, Ryne C; Roberts, Brian S; Dean, Emma C; Burwell, Todd C; Meadows, Sarah K; Cooper, Sara J; Garabedian, Michael J; Gertz, Jason; Myers, Richard M

    2016-07-11

    The liver X receptors (LXRs, NR1H2 and NR1H3) and peroxisome proliferator-activated receptor gamma (PPARG, NR1C3) nuclear receptor transcription factors (TFs) are master regulators of energy homeostasis. Intriguingly, recent studies suggest that these metabolic regulators also impact tumor cell proliferation. However, a comprehensive temporal molecular characterization of the LXR and PPARG gene regulatory responses in tumor cells is still lacking. To better define the underlying molecular processes governing the genetic control of cellular growth in response to extracellular metabolic signals, we performed a comprehensive, genome-wide characterization of the temporal regulatory cascades mediated by LXR and PPARG signaling in HT29 colorectal cancer cells. For this analysis, we applied a multi-tiered approach that incorporated cellular phenotypic assays, gene expression profiles, chromatin state dynamics, and nuclear receptor binding patterns. Our results illustrate that the activation of both nuclear receptors inhibited cell proliferation and further decreased glutathione levels, consistent with increased cellular oxidative stress. Despite a common metabolic reprogramming, the gene regulatory network programs initiated by these nuclear receptors were widely distinct. PPARG generated a rapid and short-term response while maintaining a gene activator role. By contrast, LXR signaling was prolonged, with initial, predominantly activating functions that transitioned to repressive gene regulatory activities at late time points. Through the use of a multi-tiered strategy that integrated various genomic datasets, our data illustrate that distinct gene regulatory programs elicit common phenotypic effects, highlighting the complexity of the genome. These results further provide a detailed molecular map of metabolic reprogramming in cancer cells through LXR and PPARG activation. As ligand-inducible TFs, these nuclear receptors can potentially serve as attractive therapeutic

  10. Assessment of citalopram and escitalopram on neuroblastoma cell lines: Cell toxicity and gene modulation

    Science.gov (United States)

    Sakka, Laurent; Delétage, Nathalie; Chalus, Maryse; Aissouni, Youssef; Sylvain-Vidal, Valérie; Gobron, Stéphane; Coll, Guillaume

    2017-01-01

    Selective serotonin reuptake inhibitors (SSRI) are common antidepressants which cytotoxicity has been assessed in cancers notably colorectal carcinomas and glioma cell lines. We assessed and compared the cytotoxicity of 2 SSRI, citalopram and escitalopram, on neuroblastoma cell lines. The study was performed on 2 non-MYCN amplified cell lines (rat B104 and human SH-SY5Y) and 2 human MYCN amplified cell lines (IMR32 and Kelly). Citalopram and escitalopram showed concentration-dependent cytotoxicity on all cell lines. Citalopram was more cytotoxic than escitalopram. IMR32 was the most sensitive cell line. The absence of toxicity on human primary Schwann cells demonstrated the safety of both molecules for myelin. The mechanisms of cytotoxicity were explored using gene-expression profiles and quantitative real-time PCR (qPCR). Citalopram modulated 1 502 genes and escitalopram 1 164 genes with a fold change ≥ 2. 1 021 genes were modulated by both citalopram and escitalopram; 481 genes were regulated only by citalopram while 143 genes were regulated only by escitalopram. Citalopram modulated 69 pathways (KEGG) and escitalopram 42. Ten pathways were differently modulated by citalopram and escitalopram. Citalopram drastically decreased the expression of MYBL2, BIRC5 and BARD1 poor prognosis factors of neuroblastoma with fold-changes of -107 (pescitalopram. PMID:28467792

  11. Assessment of citalopram and escitalopram on neuroblastoma cell lines. Cell toxicity and gene modulation.

    Science.gov (United States)

    Sakka, Laurent; Delétage, Nathalie; Chalus, Maryse; Aissouni, Youssef; Sylvain-Vidal, Valérie; Gobron, Stéphane; Coll, Guillaume

    2017-06-27

    Selective serotonin reuptake inhibitors (SSRI) are common antidepressants which cytotoxicity has been assessed in cancers notably colorectal carcinomas and glioma cell lines. We assessed and compared the cytotoxicity of 2 SSRI, citalopram and escitalopram, on neuroblastoma cell lines. The study was performed on 2 non-MYCN amplified cell lines (rat B104 and human SH-SY5Y) and 2 human MYCN amplified cell lines (IMR32 and Kelly). Citalopram and escitalopram showed concentration-dependent cytotoxicity on all cell lines. Citalopram was more cytotoxic than escitalopram. IMR32 was the most sensitive cell line. The absence of toxicity on human primary Schwann cells demonstrated the safety of both molecules for myelin. The mechanisms of cytotoxicity were explored using gene-expression profiles and quantitative real-time PCR (qPCR). Citalopram modulated 1 502 genes and escitalopram 1 164 genes with a fold change ≥ 2. 1 021 genes were modulated by both citalopram and escitalopram; 481 genes were regulated only by citalopram while 143 genes were regulated only by escitalopram. Citalopram modulated 69 pathways (KEGG) and escitalopram 42. Ten pathways were differently modulated by citalopram and escitalopram. Citalopram drastically decreased the expression of MYBL2, BIRC5 and BARD1 poor prognosis factors of neuroblastoma with fold-changes of -107 (pescitalopram.

  12. Human Retrotransposon Insertion Polymorphisms Are Associated with Health and Disease via Gene Regulatory Phenotypes

    Directory of Open Access Journals (Sweden)

    Lu Wang

    2017-08-01

    Full Text Available The human genome hosts several active families of transposable elements (TEs, including the Alu, LINE-1, and SVA retrotransposons that are mobilized via reverse transcription of RNA intermediates. We evaluated how insertion polymorphisms generated by human retrotransposon activity may be related to common health and disease phenotypes that have been previously interrogated through genome-wide association studies (GWAS. To address this question, we performed a genome-wide screen for retrotransposon polymorphism disease associations that are linked to TE induced gene regulatory changes. Our screen first identified polymorphic retrotransposon insertions found in linkage disequilibrium (LD with single nucleotide polymorphisms that were previously associated with common complex diseases by GWAS. We further narrowed this set of candidate disease associated retrotransposon polymorphisms by identifying insertions that are located within tissue-specific enhancer elements. We then performed expression quantitative trait loci analysis on the remaining set of candidates in order to identify polymorphic retrotransposon insertions that are associated with gene expression changes in B-cells of the human immune system. This progressive and stringent screen yielded a list of six retrotransposon insertions as the strongest candidates for TE polymorphisms that lead to disease via enhancer-mediated changes in gene regulation. For example, we found an SVA insertion within a cell-type specific enhancer located in the second intron of the B4GALT1 gene. B4GALT1 encodes a glycosyltransferase that functions in the glycosylation of the Immunoglobulin G (IgG antibody in such a way as to convert its activity from pro- to anti-inflammatory. The disruption of the B4GALT1 enhancer by the SVA insertion is associated with down-regulation of the gene in B-cells, which would serve to keep the IgG molecule in a pro-inflammatory state. Consistent with this idea, the B4GALT1 enhancer

  13. A putative regulatory genetic locus modulates virulence in the pathogen Leptospira interrogans.

    Science.gov (United States)

    Eshghi, Azad; Becam, Jérôme; Lambert, Ambroise; Sismeiro, Odile; Dillies, Marie-Agnès; Jagla, Bernd; Wunder, Elsio A; Ko, Albert I; Coppee, Jean-Yves; Goarant, Cyrille; Picardeau, Mathieu

    2014-06-01

    Limited research has been conducted on the role of transcriptional regulators in relation to virulence in Leptospira interrogans, the etiological agent of leptospirosis. Here, we identify an L. interrogans locus that encodes a sensor protein, an anti-sigma factor antagonist, and two genes encoding proteins of unknown function. Transposon insertion into the gene encoding the sensor protein led to dampened transcription of the other 3 genes in this locus. This lb139 insertion mutant (the lb139(-) mutant) displayed attenuated virulence in the hamster model of infection and reduced motility in vitro. Whole-transcriptome analyses using RNA sequencing revealed the downregulation of 115 genes and the upregulation of 28 genes, with an overrepresentation of gene products functioning in motility and signal transduction and numerous gene products with unknown functions, predicted to be localized to the extracellular space. Another significant finding encompassed suppressed expression of the majority of the genes previously demonstrated to be upregulated at physiological osmolarity, including the sphingomyelinase C precursor Sph2 and LigB. We provide insight into a possible requirement for transcriptional regulation as it relates to leptospiral virulence and suggest various biological processes that are affected due to the loss of native expression of this genetic locus.

  14. Regulatory polymorphisms in the cyclophilin A gene, PPIA, accelerate progression to AIDS.

    Directory of Open Access Journals (Sweden)

    Ping An

    2007-06-01

    Full Text Available Human cyclophilin A, or CypA, encoded by the gene peptidyl prolyl isomerase A (PPIA, is incorporated into the HIV type 1 (HIV-1 virion and promotes HIV-1 infectivity by facilitating virus uncoating. We examined the effect of single nucleotide polymorphisms (SNPs and haplotypes within the PPIA gene on HIV-1 infection and disease progression in five HIV-1 longitudinal history cohorts. Kaplan-Meier survival statistics and Cox proportional hazards model were used to assess time to AIDS outcomes. Among eight SNPs tested, two promoter SNPs (SNP3 and SNP4 in perfect linkage disequilibrium were associated with more rapid CD4(+ T-cell loss (relative hazard = 3.7, p = 0.003 in African Americans. Among European Americans, these alleles were also associated with a significant trend to more rapid progression to AIDS in a multi-point categorical analysis (p = 0.005. Both SNPs showed differential nuclear protein-binding efficiencies in a gel shift assay. In addition, one SNP (SNP5 located in the 5' UTR previously shown to be associated with higher ex vivo HIV-1 replication was found to be more frequent in HIV-1-positive individuals than in those highly exposed uninfected individuals. These results implicate regulatory PPIA polymorphisms as a component of genetic susceptibility to HIV-1 infection or disease progression, affirming the important role of PPIA in HIV-1 pathogenesis.

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

    Energy Technology Data Exchange (ETDEWEB)

    Jobert, Laure; Argentini, Manuela [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France); Tora, Laszlo, E-mail: laszlo@igbmc.u-strasbg.fr [Institut de Genetique et de Biologie Moleculaire et Cellulaire (IGBMC), CNRS UMR 7104, INSERM U 596, Universite Louis Pasteur de Strasbourg, BP 10142 - 67404 Illkirch Cedex, CU de Strasbourg (France)

    2009-04-15

    TAF15 (formerly TAF{sub II}68) is a nuclear RNA-binding protein that is associated with a distinct population of TFIID and RNA polymerase II complexes. TAF15 harbours an N-terminal activation domain, an RNA recognition motif (RRM) and many Arg-Gly-Gly (RGG) repeats at its C-terminal end. The N-terminus of TAF15 serves as an essential transforming domain in the fusion oncoprotein created by chromosomal translocation in certain human chondrosarcomas. Post-transcriptional modifications (PTMs) of proteins are known to regulate their activity, however, nothing is known on how PTMs affect TAF15 function. Here we demonstrate that endogenous human TAF15 is methylated in vivo at its numerous RGG repeats. Furthermore, we identify protein arginine N-methyltransferase 1 (PRMT1) as a TAF15 interactor and the major PRMT responsible for its methylation. In addition, the RGG repeat-containing C-terminus of TAF15 is responsible for the shuttling between the nucleus and the cytoplasm and the methylation of RGG repeats affects the subcellular localization of TAF15. The methylation of TAF15 by PRMT1 is required for the ability of TAF15 to positively regulate the expression of the studied endogenous TAF15-target genes. Our findings demonstrate that arginine methylation of TAF15 by PRMT1 is a crucial event determining its proper localization and gene regulatory function.

  16. An intersectional gene regulatory strategy defines subclass diversity of C. elegans motor neurons.

    Science.gov (United States)

    Kratsios, Paschalis; Kerk, Sze Yen; Catela, Catarina; Liang, Joseph; Vidal, Berta; Bayer, Emily A; Feng, Weidong; De La Cruz, Estanisla Daniel; Croci, Laura; Consalez, G Giacomo; Mizumoto, Kota; Hobert, Oliver

    2017-07-05

    A core principle of nervous system organization is the diversification of neuron classes into subclasses that share large sets of features but differ in select traits. We describe here a molecular mechanism necessary for motor neurons to acquire subclass-specific traits in the nematode Caenorhabditis elegans . Cholinergic motor neuron classes of the ventral nerve cord can be subdivided into subclasses along the anterior-posterior (A-P) axis based on synaptic connectivity patterns and molecular features. The conserved COE-type terminal selector UNC-3 not only controls the expression of traits shared by all members of a neuron class, but is also required for subclass-specific traits expressed along the A-P axis. UNC-3, which is not regionally restricted, requires region-specific cofactors in the form of Hox proteins to co-activate subclass-specific effector genes in post-mitotic motor neurons. This intersectional gene regulatory principle for neuronal subclass diversification may be conserved from nematodes to mice.

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

    Science.gov (United States)

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case.

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

    International Nuclear Information System (INIS)

    Jobert, Laure; Argentini, Manuela; Tora, Laszlo

    2009-01-01

    TAF15 (formerly TAF 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.

  19. Sieve-based relation extraction of gene regulatory networks from biological literature.

    Science.gov (United States)

    Žitnik, Slavko; Žitnik, Marinka; Zupan, Blaž; Bajec, Marko

    2015-01-01

    Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To extract them in an explicit, computer readable format, these relations were at first extracted manually from databases. Manual curation was later replaced with automatic or semi-automatic tools with natural language processing capabilities. The current challenge is the development of information extraction procedures that can directly infer more complex relational structures, such as gene regulatory networks. We develop a computational approach for extraction of gene regulatory networks from textual data. Our method is designed as a sieve-based system and uses linear-chain conditional random fields and rules for relation extraction. With this method we successfully extracted the sporulation gene regulation network in the bacterium Bacillus subtilis for the information extraction challenge at the BioNLP 2013 conference. To enable extraction of distant relations using first-order models, we transform the data into skip-mention sequences. We infer multiple models, each of which is able to extract different relationship types. Following the shared task, we conducted additional analysis using different system settings that resulted in reducing the reconstruction error of bacterial sporulation network from 0.73 to 0.68, measured as the slot error rate between the predicted and the reference network. We observe that all relation extraction sieves contribute to the predictive performance of the proposed approach. Also, features constructed by considering mention words and their prefixes and suffixes are the most important features for higher accuracy of extraction. Analysis of distances between different mention types in the text shows that our choice of transforming

  20. Gene Targeting and Expression Modulation by Peptide Nucleic Acids (PNA)

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    Peptide nucleic acids (PNA) are artificial structural mimics of nucleic acids capable of sequence specific hybridization to both RNA and DNA. Thus they have obvious potential as gene targeting agents for drug discovery approaches. An overview with emphasis on recent progress on RNA "interference...

  1. Meta-analysis of peripheral blood gene expression modules for COPD phenotypes.

    Directory of Open Access Journals (Sweden)

    Dominik Reinhold

    Full Text Available Chronic obstructive pulmonary disease (COPD occurs typically in current or former smokers, but only a minority of people with smoking history develops the disease. Besides environmental factors, genetics is an important risk factor for COPD. However, the relationship between genetics, environment and phenotypes is not well understood. Sample sizes for genome-wide expression studies based on lung tissue have been small due to the invasive nature of sample collection. Increasing evidence for the systemic nature of the disease makes blood a good alternative source to study the disease, but there have also been few large-scale blood genomic studies in COPD. Due to the complexity and heterogeneity of COPD, examining groups of interacting genes may have more relevance than identifying individual genes. Therefore, we used Weighted Gene Co-expression Network Analysis to find groups of genes (modules that are highly connected. However, module definitions may vary between individual data sets. To alleviate this problem, we used a consensus module definition based on two cohorts, COPDGene and ECLIPSE. We studied the relationship between the consensus modules and COPD phenotypes airflow obstruction and emphysema. We also used these consensus module definitions on an independent cohort (TESRA and performed a meta analysis involving all data sets. We found several modules that are associated with COPD phenotypes, are enriched in functional categories and are overrepresented for cell-type specific genes. Of the 14 consensus modules, three were strongly associated with airflow obstruction (meta p ≤ 0.0002, and two had some association with emphysema (meta p ≤ 0.06; some associations were stronger in the case-control cohorts, and others in the cases-only subcohorts. Gene Ontology terms that were overrepresented included "immune response" and "defense response." The cell types whose type-specific genes were overrepresented in modules (p < 0.05 included

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

    Science.gov (United States)

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

    2015-12-01

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

  3. Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence

    NARCIS (Netherlands)

    Jing, Hai-Chun; Anderson, Lisa; Sturre, Marcel J. G.; Hille, Jacques; Dijkwel, Paul P.

    2007-01-01

    Arabidopsis CPR5 is a senescence-regulatory gene with pleiotropic functions as predicted by the evolutionary theory of senescence Hai-Chun Jing1,2, Lisa Anderson3, Marcel J.G. Sturre1, Jacques Hille1 and Paul P. Dijkwel1,* 1Molecular Biology of Plants, Groningen Biomolecular Sciences and

  4. Structural basis for regulation of rhizobial nodulation and symbiosis gene expression by the regulatory NolR

    Science.gov (United States)

    The symbiosis between rhizobial microbes and host plants involves the coordinated expression of multiple genes, which leads to nodule formation and nitrogen fixation. As part of the transcriptional machinery for nodulation and symbiosis across a range of Rhizobium, NolR serves as a global regulatory...

  5. Coronavirus gene 7 counteracts host defenses and modulates virus virulence.

    Directory of Open Access Journals (Sweden)

    Jazmina L G Cruz

    2011-06-01

    Full Text Available Transmissible gastroenteritis virus (TGEV genome contains three accessory genes: 3a, 3b and 7. Gene 7 is only present in members of coronavirus genus a1, and encodes a hydrophobic protein of 78 aa. To study gene 7 function, a recombinant TGEV virus lacking gene 7 was engineered (rTGEV-Δ7. Both the mutant and the parental (rTGEV-wt viruses showed the same growth and viral RNA accumulation kinetics in tissue cultures. Nevertheless, cells infected with rTGEV-Δ7 virus showed an increased cytopathic effect caused by an enhanced apoptosis mediated by caspase activation. Macromolecular synthesis analysis showed that rTGEV-Δ7 virus infection led to host translational shut-off and increased cellular RNA degradation compared with rTGEV-wt infection. An increase of eukaryotic translation initiation factor 2 (eIF2α phosphorylation and an enhanced nuclease, most likely RNase L, activity were observed in rTGEV-Δ7 virus infected cells. These results suggested that the removal of gene 7 promoted an intensified dsRNA-activated host antiviral response. In protein 7 a conserved sequence motif that potentially mediates binding to protein phosphatase 1 catalytic subunit (PP1c, a key regulator of the cell antiviral defenses, was identified. We postulated that TGEV protein 7 may counteract host antiviral response by its association with PP1c. In fact, pull-down assays demonstrated the interaction between TGEV protein 7, but not a protein 7 mutant lacking PP1c binding motif, with PP1. Moreover, the interaction between protein 7 and PP1 was required, during the infection, for eIF2α dephosphorylation and inhibition of cell RNA degradation. Inoculation of newborn piglets with rTGEV-Δ7 and rTGEV-wt viruses showed that rTGEV-Δ7 virus presented accelerated growth kinetics and pathology compared with the parental virus. Overall, the results indicated that gene 7 counteracted host cell defenses, and modified TGEV persistence increasing TGEV survival. Therefore, the

  6. Investigation of epigenetic gene regulation in Arabidopsis modulated by gamma radiation

    International Nuclear Information System (INIS)

    Woo, Hye Ryun; Kim, Jae Sung; Lee, Myung Jin; Lee, Dong Joon; Kim, Young Min; Jung, Joon Yong; Han, Wan Keun; Kang, Soo Jin

    2011-12-01

    To investigate epigenetic gene regulation in Arabidopsis modulated by gamma radiation, we examined the changes in DNA methylation and histone modification after gamma radiation and investigated the effects of gamma radiation on epigenetic information and gene expression. We have selected 14 genes with changes in DNA methylation by gamma radiation, analyzed the changes of histone modification in the selected genes to reveal the relationship between DNA methylation and histone modification by gamma radiation. We have also analyzed the effects of gamma radiation on gene expression to investigate the relationship between epigenetic information and gene expression by gamma radiation. The results will be useful to reveal the effects of gamma radiation on DNA methylation, histone modification and gene expression. We anticipate that the information generated in this proposal will help to find out the mechanism underlying the changes in epigenetic information by gamma radiation

  7. Inherited variants in regulatory T cell genes and outcome of ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Ellen L Goode

    Full Text Available Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL and sequence-based tagging single nucleotide polymorphisms (tagSNPs for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p=2.7×10(-5, LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.5×10(-4, and rs3753348, p=9.0×10(-4, respectively, and CD80 (endometrioid, rs13071247, p=8.0×10(-4. Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p=0.006. An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p=8.1×10(-4 among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.

  8. Inherited variants in regulatory T cell genes and outcome of ovarian cancer.

    Science.gov (United States)

    Goode, Ellen L; DeRycke, Melissa; Kalli, Kimberly R; Oberg, Ann L; Cunningham, Julie M; Maurer, Matthew J; Fridley, Brooke L; Armasu, Sebastian M; Serie, Daniel J; Ramar, Priya; Goergen, Krista; Vierkant, Robert A; Rider, David N; Sicotte, Hugues; Wang, Chen; Winterhoff, Boris; Phelan, Catherine M; Schildkraut, Joellen M; Weber, Rachel P; Iversen, Ed; Berchuck, Andrew; Sutphen, Rebecca; Birrer, Michael J; Hampras, Shalaka; Preus, Leah; Gayther, Simon A; Ramus, Susan J; Wentzensen, Nicolas; Yang, Hannah P; Garcia-Closas, Montserrat; Song, Honglin; Tyrer, Jonathan; Pharoah, Paul P D; Konecny, Gottfried; Sellers, Thomas A; Ness, Roberta B; Sucheston, Lara E; Odunsi, Kunle; Hartmann, Lynn C; Moysich, Kirsten B; Knutson, Keith L

    2013-01-01

    Although ovarian cancer is the most lethal of gynecologic malignancies, wide variation in outcome following conventional therapy continues to exist. The presence of tumor-infiltrating regulatory T cells (Tregs) has a role in outcome of this disease, and a growing body of data supports the existence of inherited prognostic factors. However, the role of inherited variants in genes encoding Treg-related immune molecules has not been fully explored. We analyzed expression quantitative trait loci (eQTL) and sequence-based tagging single nucleotide polymorphisms (tagSNPs) for 54 genes associated with Tregs in 3,662 invasive ovarian cancer cases. With adjustment for known prognostic factors, suggestive results were observed among rarer histological subtypes; poorer survival was associated with minor alleles at SNPs in RGS1 (clear cell, rs10921202, p=2.7×10(-5)), LRRC32 and TNFRSF18/TNFRSF4 (mucinous, rs3781699, p=4.5×10(-4), and rs3753348, p=9.0×10(-4), respectively), and CD80 (endometrioid, rs13071247, p=8.0×10(-4)). Fo0r the latter, correlative data support a CD80 rs13071247 genotype association with CD80 tumor RNA expression (p=0.006). An additional eQTL SNP in CD80 was associated with shorter survival (rs7804190, p=8.1×10(-4)) among all cases combined. As the products of these genes are known to affect induction, trafficking, or immunosuppressive function of Tregs, these results suggest the need for follow-up phenotypic studies.

  9. A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Xiangyun Xiao

    Full Text Available The reconstruction of gene regulatory networks (GRNs from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM, experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

  10. A new asynchronous parallel algorithm for inferring large-scale gene regulatory networks.

    Science.gov (United States)

    Xiao, Xiangyun; Zhang, Wei; Zou, Xiufen

    2015-01-01

    The reconstruction of gene regulatory networks (GRNs) from high-throughput experimental data has been considered one of the most important issues in systems biology research. With the development of high-throughput technology and the complexity of biological problems, we need to reconstruct GRNs that contain thousands of genes. However, when many existing algorithms are used to handle these large-scale problems, they will encounter two important issues: low accuracy and high computational cost. To overcome these difficulties, the main goal of this study is to design an effective parallel algorithm to infer large-scale GRNs based on high-performance parallel computing environments. In this study, we proposed a novel asynchronous parallel framework to improve the accuracy and lower the time complexity of large-scale GRN inference by combining splitting technology and ordinary differential equation (ODE)-based optimization. The presented algorithm uses the sparsity and modularity of GRNs to split whole large-scale GRNs into many small-scale modular subnetworks. Through the ODE-based optimization of all subnetworks in parallel and their asynchronous communications, we can easily obtain the parameters of the whole network. To test the performance of the proposed approach, we used well-known benchmark datasets from Dialogue for Reverse Engineering Assessments and Methods challenge (DREAM), experimentally determined GRN of Escherichia coli and one published dataset that contains more than 10 thousand genes to compare the proposed approach with several popular algorithms on the same high-performance computing environments in terms of both accuracy and time complexity. The numerical results demonstrate that our parallel algorithm exhibits obvious superiority in inferring large-scale GRNs.

  11. CHIR99021 promotes self-renewal of mouse embryonic stem cells by modulation of protein-encoding gene and long intergenic non-coding RNA expression

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Yongyan [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Ai, Zhiying [Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); College of Life Sciences, Northwest A and F University, Yangling 712100, Shaanxi (China); Yao, Kezhen [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Cao, Lixia; Du, Juan; Shi, Xiaoyan [Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); College of Life Sciences, Northwest A and F University, Yangling 712100, Shaanxi (China); Guo, Zekun, E-mail: gzk@nwsuaf.edu.cn [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China); Zhang, Yong, E-mail: zhylab@hotmail.com [College of Veterinary Medicine, Northwest A and F University, Yangling 712100, Shaanxi (China); Key Laboratory of Animal Biotechnology, Ministry of Agriculture, Northwest A and F University, Yangling 712100, Shaanxi (China)

    2013-10-15

    Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway by stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network. - Highlights: • Combined use of CHIR with LIF promotes self-renewal of J1 mESCs. • CHIR-regulated genes are involved in multiple pathways. • CHIR inhibits Nodal signaling and promotes Bmp4 expression to activate BMP signaling. • Expression of epigenetic regulatory genes and lincRNAs is altered by CHIR.

  12. CHIR99021 promotes self-renewal of mouse embryonic stem cells by modulation of protein-encoding gene and long intergenic non-coding RNA expression

    International Nuclear Information System (INIS)

    Wu, Yongyan; Ai, Zhiying; Yao, Kezhen; Cao, Lixia; Du, Juan; Shi, Xiaoyan; Guo, Zekun; Zhang, Yong

    2013-01-01

    Embryonic stem cells (ESCs) can proliferate indefinitely in vitro and differentiate into cells of all three germ layers. These unique properties make them exceptionally valuable for drug discovery and regenerative medicine. However, the practical application of ESCs is limited because it is difficult to derive and culture ESCs. It has been demonstrated that CHIR99021 (CHIR) promotes self-renewal and enhances the derivation efficiency of mouse (m)ESCs. However, the downstream targets of CHIR are not fully understood. In this study, we identified CHIR-regulated genes in mESCs using microarray analysis. Our microarray data demonstrated that CHIR not only influenced the Wnt/β-catenin pathway by stabilizing β-catenin, but also modulated several other pluripotency-related signaling pathways such as TGF-β, Notch and MAPK signaling pathways. More detailed analysis demonstrated that CHIR inhibited Nodal signaling, while activating bone morphogenetic protein signaling in mESCs. In addition, we found that pluripotency-maintaining transcription factors were up-regulated by CHIR, while several developmental-related genes were down-regulated. Furthermore, we found that CHIR altered the expression of epigenetic regulatory genes and long intergenic non-coding RNAs. Quantitative real-time PCR results were consistent with microarray data, suggesting that CHIR alters the expression pattern of protein-encoding genes (especially transcription factors), epigenetic regulatory genes and non-coding RNAs to establish a relatively stable pluripotency-maintaining network. - Highlights: • Combined use of CHIR with LIF promotes self-renewal of J1 mESCs. • CHIR-regulated genes are involved in multiple pathways. • CHIR inhibits Nodal signaling and promotes Bmp4 expression to activate BMP signaling. • Expression of epigenetic regulatory genes and lincRNAs is altered by CHIR

  13. Selective AR Modulators that Distinguish Proliferative from Differentiative Gene Promoters

    Science.gov (United States)

    2016-08-01

    levels, and in some cases be useful in early stage disease or watchful waiting, and in other cases castration resistant prostate cancer (CRPC...dependent kinase inhibitor p21 gene through an androgen response element in the proximal promoter. Molecular endocrinology 13, 376 (Mar, 1999). 9...analyses and in mouse xenograft experiments, as planned. We will also continue to probe the molecular mechanism by which dox elicits these differential

  14. DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

    Science.gov (United States)

    Gerstein, Mark

    2016-01-01

    Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

  15. DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

    Directory of Open Access Journals (Sweden)

    Daifeng Wang

    2016-10-01

    Full Text Available Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs, cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal and another subsystem's (external gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs, seeing the degree to which these can be accounted for by orthologous (internal versus species-specific (external TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

  16. A gene regulatory network controlling hhex transcription in the anterior endoderm of the organizer

    Science.gov (United States)

    Rankin, Scott A.; Kormish, Jay; Kofron, Matt; Jegga, Anil; Zorn, Aaron M.

    2011-01-01

    The homeobox gene hhex is one of the earliest markers of the anterior endoderm, which gives rise to foregut organs such as the liver, ventral pancreas, thyroid, and lungs. The regulatory networks controlling hhex transcription are poorly understood. In an extensive cis-regulatory analysis of the Xenopus hhex promoter we determined how the Nodal, Wnt, and BMP pathways and their downstream transcription factors regulate hhex expression in the gastrula organizer. We show that Nodal signaling, present throughout the endoderm, directly activates hhex transcription via FoxH1/Smad2 binding sites in the proximal −0.44 Kb promoter. This positive action of Nodal is suppressed in the ventral-posterior endoderm by Vent 1 and Vent2, homeodomain repressors that are induced by BMP signaling. Maternal Wnt/β-catenin on the dorsal side of the embryo cooperates with Nodal and indirectly activate hhex expression via the homeodomain activators Siamois and Twin. Siamois/Twin stimulate hhex transcription through two mechanisms: 1) They induce the expression of Otx2 and Lim1 and together Siamois, Twin, Otx2 and Lim1 appear to promote hhex transcription through homeobox sites in a Wnt-responsive element located between −0.65 to −0.55 Kb of the hhex promoter. 2) Siamois/Twin also induce the expression of the BMP-antagonists Chordin and Noggin, which are required to exclude Vents from the organizer allowing hhex transcription. This work reveals a complex network regulating anterior endoderm transcription in the early embryo. PMID:21215263

  17. A Kalman-filter based approach to identification of time-varying gene regulatory networks.

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    Jie Xiong

    Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

  18. Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

    Science.gov (United States)

    Farber, Charles R

    2010-11-01

    Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD. © 2010 American Society for Bone and Mineral Research.

  19. Liver X Receptor Agonists Inhibit the Phospholipid Regulatory Gene CTP: Phosphoethanolamine Cytidylyltransferase-Pcyt2

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    Lin Zhu

    2008-01-01

    Full Text Available Metabolic pulse-chase experiments demonstrated that 25-hydroxycholesterol (25-OH, the endogenous activator of the liver X receptor (LXR, significantly reduced the biosynthesis of phosphatidylethanolamine via CDP-ethanolamine (Kennedy pathway at the step catalyzed by CTP: phosphoethanolamine cytidylyltransferase (Pcyt2. In the mouse embryonic fibroblasts C3H10T1/2, the LXR synthetic agonist TO901317 lowered Pcyt2 promoter-luciferase activity in a concentration-dependent manner. Furthermore, 25-OH and TO901317 reduced mouse Pcyt2 mRNA and protein levels by 35–60%. The inhibitory effects of oxysterols and TO901317 on the Pcyt2 promoter function, mRNA and protein expression were conserved in the human breast cancer cells MCF-7. These studies identify the Pcyt2 gene as a novel target whereby LXR agonists may indirectly modulate inflammatory responses and atherosclerosis.

  20. Dynamic in vivo binding of transcription factors to cis-regulatory modules of cer and gsc in the stepwise formation of the Spemann–Mangold organizer

    Science.gov (United States)

    Sudou, Norihiro; Yamamoto, Shinji; Ogino, Hajime; Taira, Masanori

    2012-01-01

    How multiple developmental cues are integrated on cis-regulatory modules (CRMs) for cell fate decisions remains uncertain. The Spemann–Mangold organizer in Xenopus embryos expresses the transcription factors Lim1/Lhx1, Otx2, Mix1, Siamois (Sia) and VegT. Reporter analyses using sperm nuclear transplantation and DNA injection showed that cerberus (cer) and goosecoid (gsc) are activated by the aforementioned transcription factors through CRMs conserved between X. laevis and X. tropicalis. ChIP-qPCR analysis for the five transcription factors revealed that cer and gsc CRMs are initially bound by both Sia and VegT at the late blastula stage, and subsequently bound by all five factors at the gastrula stage. At the neurula stage, only binding of Lim1 and Otx2 to the gsc CRM, among others, persists, which corresponds to their co-expression in the prechordal plate. Based on these data, together with detailed expression pattern analysis, we propose a new model of stepwise formation of the organizer, in which (1) maternal VegT and Wnt-induced Sia first bind to CRMs at the blastula stage; then (2) Nodal-inducible Lim1, Otx2, Mix1 and zygotic VegT are bound to CRMs in the dorsal endodermal and mesodermal regions where all these genes are co-expressed; and (3) these two regions are combined at the gastrula stage to form the organizer. Thus, the in vivo dynamics of multiple transcription factors highlight their roles in the initiation and maintenance of gene expression, and also reveal the stepwise integration of maternal, Nodal and Wnt signaling on CRMs of organizer genes to generate the organizer. PMID:22492356

  1. Dynamic in vivo binding of transcription factors to cis-regulatory modules of cer and gsc in the stepwise formation of the Spemann-Mangold organizer.

    Science.gov (United States)

    Sudou, Norihiro; Yamamoto, Shinji; Ogino, Hajime; Taira, Masanori

    2012-05-01

    How multiple developmental cues are integrated on cis-regulatory modules (CRMs) for cell fate decisions remains uncertain. The Spemann-Mangold organizer in Xenopus embryos expresses the transcription factors Lim1/Lhx1, Otx2, Mix1, Siamois (Sia) and VegT. Reporter analyses using sperm nuclear transplantation and DNA injection showed that cerberus (cer) and goosecoid (gsc) are activated by the aforementioned transcription factors through CRMs conserved between X. laevis and X. tropicalis. ChIP-qPCR analysis for the five transcription factors revealed that cer and gsc CRMs are initially bound by both Sia and VegT at the late blastula stage, and subsequently bound by all five factors at the gastrula stage. At the neurula stage, only binding of Lim1 and Otx2 to the gsc CRM, among others, persists, which corresponds to their co-expression in the prechordal plate. Based on these data, together with detailed expression pattern analysis, we propose a new model of stepwise formation of the organizer, in which (1) maternal VegT and Wnt-induced Sia first bind to CRMs at the blastula stage; then (2) Nodal-inducible Lim1, Otx2, Mix1 and zygotic VegT are bound to CRMs in the dorsal endodermal and mesodermal regions where all these genes are co-expressed; and (3) these two regions are combined at the gastrula stage to form the organizer. Thus, the in vivo dynamics of multiple transcription factors highlight their roles in the initiation and maintenance of gene expression, and also reveal the stepwise integration of maternal, Nodal and Wnt signaling on CRMs of organizer genes to generate the organizer.

  2. Integration of TP53, DREAM, MMB-FOXM1 and RB-E2F target gene analyses identifies cell cycle gene regulatory networks.

    Science.gov (United States)

    Fischer, Martin; Grossmann, Patrick; Padi, Megha; DeCaprio, James A

    2016-07-27

    Cell cycle (CC) and TP53 regulatory networks are frequently deregulated in cancer. While numerous genome-wide studies of TP53 and CC-regulated genes have been performed, significant variation between studies has made it difficult to assess regulation of any given gene of interest. To overcome the limitation of individual studies, we developed a meta-analysis approach to identify high confidence target genes that reflect their frequency of identification in independent datasets. Gene regulatory networks were generated by comparing differential expression of TP53 and CC-regulated genes with chromatin immunoprecipitation studies for TP53, RB1, E2F, DREAM, B-MYB, FOXM1 and MuvB. RNA-seq data from p21-null cells revealed that gene downregulation by TP53 generally requires p21 (CDKN1A). Genes downregulated by TP53 were also identified as CC genes bound by the DREAM complex. The transcription factors RB, E2F1 and E2F7 bind to a subset of DREAM target genes that function in G1/S of the CC while B-MYB, FOXM1 and MuvB control G2/M gene expression. Our approach yields high confidence ranked target gene maps for TP53, DREAM, MMB-FOXM1 and RB-E2F and enables prediction and distinction of CC regulation. A web-based atlas at www.targetgenereg.org enables assessing the regulation of any human gene of interest. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  3. Estrogen protection against EAE modulates the microbiota and mucosal-associated regulatory cells.

    Science.gov (United States)

    Benedek, Gil; Zhang, Jun; Nguyen, Ha; Kent, Gail; Seifert, Hilary A; Davin, Sean; Stauffer, Patrick; Vandenbark, Arthur A; Karstens, Lisa; Asquith, Mark; Offner, Halina

    2017-09-15

    Sex hormones promote immunoregulatory effects on multiple sclerosis. In the current study we evaluated the composition of the gut microbiota and the mucosal-associated regulatory cells in estrogen or sham treated female mice before and after autoimmune encephalomyelitis (EAE) induction. Treatment with pregnancy levels of estrogen induces changes in the composition and diversity of gut microbiota. Additionally, estrogen prevents EAE-associated changes in the gut microbiota and might promote the enrichment of bacteria that are associated with immune regulation. Our results point to a possible cross-talk between the sex hormones and the gut microbiota, which could promote neuroprotection. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. A microRNA-mediated regulatory loop modulates NOTCH and MYC oncogenic signals in B- and T-cell malignancies.

    Science.gov (United States)

    Ortega, M; Bhatnagar, H; Lin, A-P; Wang, L; Aster, J C; Sill, H; Aguiar, R C T

    2015-04-01

    Growing evidence suggests that microRNAs (miRNAs) facilitate the cross-talk between transcriptional modules and signal transduction pathways. MYC and NOTCH1 contribute to the pathogenesis of lymphoid malignancies. NOTCH induces MYC, connecting two signaling programs that enhance oncogenicity. Here we show that this relationship is bidirectional and that MYC, via a miRNA intermediary, modulates NOTCH. MicroRNA-30a (miR-30a), a member of a family of miRNAs that are transcriptionally suppressed by MYC, directly binds to and inhibits NOTCH1 and NOTCH2 expression. Using a murine model and genetically modified human cell lines, we confirmed that miR-30a influences NOTCH expression in a MYC-dependent fashion. In turn, through genetic modulation, we demonstrated that intracellular NOTCH1 and NOTCH2, by inducing MYC, suppressed miR-30a. Conversely, pharmacological inhibition of NOTCH decreased MYC expression and ultimately de-repressed miR-30a. Examination of genetic models of gain and loss of miR-30a in diffuse large B-cell lymphoma (DLBCL) and T-acute lymphoblastic leukemia (T-ALL) cells suggested a tumor-suppressive role for this miRNA. Finally, the activity of the miR-30a-NOTCH-MYC loop was validated in primary DLBCL and T-ALL samples. These data define the presence of a miRNA-mediated regulatory circuitry that may modulate the oncogenic signals originating from NOTCH and MYC.

  5. Gene Network for Identifying the Entropy Changes of Different Modules in Pediatric Sepsis

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    Jing Yang

    2016-12-01

    Full Text Available Background/Aims: Pediatric sepsis is a disease that threatens life of children. The incidence of pediatric sepsis is higher in developing countries due to various reasons, such as insufficient immunization and nutrition, water and air pollution, etc. Exploring the potential genes via different methods is of significance for the prevention and treatment of pediatric sepsis. This study aimed to identify potential genes associated with pediatric sepsis utilizing analysis of gene network and entropy. Methods: The mRNA expression in the blood samples collected from 20 septic children and 30 healthy controls was quantified by using Affymetrix HG-U133A microarray. Two condition-specific protein-protein interaction networks (PINs, one for the healthy control and the other one for the children with sepsis, were deduced by combining the fundamental human PINs with gene expression profiles in the two phenotypes. Subsequently, distinct modules from the two conditional networks were extracted by adopting a maximal clique-merging approach. Delta entropy (ΔS was calculated between sepsis and control modules. Results: Then, key genes displaying changes in gene composition were identified by matching the control and sepsis modules. Two objective modules were obtained, in which ribosomal protein RPL4 and RPL9 as well as TOP2A were probably considered as the key genes differentiating sepsis from healthy controls. Conclusion: According to previous reports and this work, TOP2A is the potential gene therapy target for pediatric sepsis. The relationship between pediatric sepsis and RPL4 and RPL9 needs further investigation.

  6. Chloroquine mediated modulation of Anopheles gambiae gene expression.

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    Patrícia Abrantes

    2008-07-01

    Full Text Available Plasmodium development in the mosquito is crucial for malaria transmission and depends on the parasite's interaction with a variety of cell types and specific mosquito factors that have both positive and negative effects on infection. Whereas the defensive response of the mosquito contributes to a decrease in parasite numbers during these stages, some components of the blood meal are known to favor infection, potentiating the risk of increased transmission. The presence of the antimalarial drug chloroquine in the mosquito's blood meal has been associated with an increase in Plasmodium infectivity for the mosquito, which is possibly caused by chloroquine interfering with the capacity of the mosquito to defend against the infection.In this study, we report a detailed survey of the Anopheles gambiae genes that are differentially regulated by the presence of chloroquine in the blood meal, using an A. gambiae cDNA microarray. The effect of chloroquine on transcript abundance was evaluated separately for non-infected and Plasmodium berghei-infected mosquitoes. Chloroquine was found to affect the abundance of transcripts that encode proteins involved in a variety of processes, including immunity, apoptosis, cytoskeleton and the response to oxidative stress. This pattern of differential gene expression may explain the weakened mosquito defense response which accounts for the increased infectivity observed in chloroquine-treated mosquitoes.The results of the present study suggest that chloroquine can interfere with several putative mosquito mechanisms of defense against Plasmodium at the level of gene expression and highlight the need for a better understanding of the impacts of antimalarial agents on parasite transmission.

  7. The WWOX Gene Modulates HDL and Lipid Metabolism

    Science.gov (United States)

    Iatan, Iulia; Choi, Hong Y.; Ruel, Isabelle; Linga Reddy, M.V. Prasad; Kil, Hyunsuk; Lee, Jaeho; Abu Odeh, Mohammad; Salah, Zaidoun; Abu-Remaileh, Muhannad; Weissglas-Volkov, Daphna; Nikkola, Elina; Civelek, Mete; Awan, Zuhier; Croce, Carlo M.; Aqeilan, Rami I.; Pajukanta, Päivi; Aldaz, C. Marcelo; Genest, Jacques

    2014-01-01

    Background Low high-density lipoprotein-cholesterol (HDL-C) constitutes a major risk factor for atherosclerosis. Recent studies from our group reported a genetic association between the WW domain-containing oxidoreductase (WWOX) gene and HDL-C levels. Here, through next-generation resequencing, in vivo functional studies and gene microarray analyses, we investigated the role of WWOX in HDL and lipid metabolism. Methods and Results Using next-generation resequencing of the WWOX region, we first identified 8 variants significantly associated and perfectly segregating with the low-HDL trait in two multi-generational French Canadian dyslipidemic families. To understand in vivo functions of WWOX, we used liver-specific Wwoxhep−/− and total Wwox−/− mice models, where we found decreased ApoA-I and ABCA1 levels in hepatic tissues. Analyses of lipoprotein profiles in Wwox−/−, but not Wwox hep−/− littermates, also showed marked reductions in serum HDL-C concentrations, concordant with the low-HDL findings observed in families. We next obtained evidence of a gender-specific effect in female Wwoxhep−/− mice, where an increase in plasma triglycerides and altered lipid metabolic pathways by microarray analyses were observed. We further identified a significant reduction in ApoA-I and LPL, and upregulation in Fas, Angptl4 and Lipg, suggesting that the effects of Wwox involve multiple pathways, including cholesterol homeostasis, ApoA-I/ABCA1 pathway, and fatty acid biosynthesis/triglyceride metabolism. Conclusions Our data indicate that WWOX disruption alters HDL and lipoprotein metabolism through several mechanisms and may account for the low-HDL phenotype observed in families expressing the WWOX variants. These findings thus describe a novel gene involved in cellular lipid homeostasis, which effects may impact atherosclerotic disease development. PMID:24871327

  8. Violacein Treatment Modulates Acute and Chronic Inflammation through the Suppression of Cytokine Production and Induction of Regulatory T Cells.

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    Liana Verinaud

    Full Text Available Inflammation is a necessary process to control infection. However, exacerbated inflammation, acute or chronic, promotes deleterious effects in the organism. Violacein (viola, a quorum sensing metabolite from the Gram-negative bacterium Chromobacterium violaceum, has been shown to protect mice from malaria and to have beneficial effects on tumors. However, it is not known whether this drug possesses anti-inflammatory activity. In this study, we investigated whether viola administration is able to reduce acute and chronic autoimmune inflammation. For that purpose, C57BL/6 mice were intraperitoneally injected with 1 μg of LPS and were treated with viola (3.5mg/kg via i.p. at the same time-point. Three hours later, the levels of inflammatory cytokines in the sera and phenotypical characterization of leukocytes were determined. Mice treated with viola presented a significant reduction in the production of inflammatory cytokines compared with untreated mice. Interestingly, although viola is a compound derived from bacteria, it did not induce inflammation upon administration to naïve mice. To test whether viola would protect mice from an autoimmune inflammation, Experimental Autoimmune Encephalomyelitis (EAE-inflicted mice were given viola i.p. at disease onset, at the 10th day from immunization. Viola-treated mice developed mild EAE disease in contrast with placebo-treated mice. The frequencies of dendritic cells and macrophages were unaltered in EAE mice treated with viola. However, the sole administration of viola augmented the levels of splenic regulatory T cells (CD4+Foxp3+. We also found that adoptive transfer of viola-elicited regulatory T cells significantly reduced EAE. Our study shows, for the first time, that violacein is able to modulate acute and chronic inflammation. Amelioration relied in suppression of cytokine production (in acute inflammation and stimulation of regulatory T cells (in chronic inflammation. New studies must be

  9. Inhibition effect of B7-H1 gene-modified regulatory dendritic cells on thyroid-associated ophthalmopathy in mice

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    Hua-Xin Chen

    2014-10-01

    Full Text Available AIM:To construct adenovirus vector expressing mice B7-H1 gene, transfect dendritic cells(DCs, and to study the therapeutic effect of modified DC on thyroid-associated ophthalmopathy(TAOin mice.METHODS: We designed and constructed B7-H1 gene adenovirus expression vector, and transfected DCs from mouse bone marrow, tested the phenotype and function of modified DCs, identificated its negative regulation to immune responses. The modified DCs were infected the sicked mice. And then the immunotherapeutic effect of modified DCs to TAO were tested. RESULTS: B7-H1 gene adenovirus vector was constructed and transfected DCs from bone marrow. The titer of the recombinant adenovirus was 1.8×109PFU/mL. B7-H1 gene modified DCs characteristics of regulatory DCs, could inhibit positive immune responses. The inhibition proceeding of TAO into mice infected modified DCs, was obviously prior to the control mice. The gene modified DCs, maybe become the new immunotherapy biological agent to thy TAO.CONCLUSION: We constructed the expression of mouse B7-H1 gene adenovirus expressed vector successfully, transfected DCs,by vector have properties of regulatory DCs, inhibiting positive immune response and the occurrence and development of thyroid eye disease. Gene modified DCs, reveal potent to the treatment of thyroid eye disease.

  10. Spaceflight modulates gene expression in the whole blood of astronauts.

    Science.gov (United States)

    Barrila, Jennifer; Ott, C Mark; LeBlanc, Carly; Mehta, Satish K; Crabbé, Aurélie; Stafford, Phillip; Pierson, Duane L; Nickerson, Cheryl A

    2016-01-01

    Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1 , HSP27 , GPX1 , XRCC1 , BAG-1 , HHR23A , FAP48 , and C-FOS . No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.

  11. Inflammatory gene regulatory networks in amnion cells following cytokine stimulation: translational systems approach to modeling human parturition.

    Directory of Open Access Journals (Sweden)

    Ruth Li

    Full Text Available A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals.

  12. A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

    Science.gov (United States)

    Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

    2018-07-01

    A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

  13. Examination of HFE associations with childhood leukemia risk and extension to other iron regulatory genes.

    Science.gov (United States)

    Kennedy, Amy E; Kamdar, Kala Y; Lupo, Philip J; Okcu, M Fatih; Scheurer, Michael E; Baum, Marianna K; Dorak, M Tevfik

    2014-09-01

    Hereditary hemochromatosis (HFE) variants correlating with body iron levels have shown associations with cancer risk, including childhood acute lymphoblastic leukemia (ALL). Using a multi-ethnic sample of cases and controls from Houston, TX, we examined two HFE variants (rs1800562 and rs1799945), one transferrin receptor gene (TFRC) variant (rs3817672) and three additional iron regulatory gene (IRG) variants (SLC11A2 rs422982; TMPRSS6 rs855791 and rs733655) for their associations with childhood ALL. Being positive for either of the HFE variants yielded a modestly elevated odds ratio (OR) for childhood ALL risk in males (1.40, 95% CI=0.83-2.35), which increased to 2.96 (95% CI=1.29-6.80) in the presence of a particular TFRC genotype for rs3817672 (P interaction=0.04). The TFRC genotype also showed an ethnicity-specific association, with increased risk observed in non-Hispanic Whites (OR=2.54, 95% CI=1.05-6.12; P interaction with ethnicity=0.02). The three additional IRG SNPs all showed individual risk associations with childhood ALL in males (OR=1.52-2.60). A polygenic model based on the number of variant alleles in five IRG SNPs revealed a linear increase in risk among males with the increasing number of variants possessed (OR=2.0 per incremental change, 95% CI=1.29-3.12; P=0.002). Our results replicated previous HFE risk associations with childhood ALL in a US population and demonstrated novel associations for IRG SNPs, thereby strengthening the hypothesis that iron excess mediated by genetic variants contributes to childhood ALL risk. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Antagonistic Coevolution Drives Whack-a-Mole Sensitivity in Gene Regulatory Networks.

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    Jeewoen Shin

    2015-10-01

    Full Text Available Robustness, defined as tolerance to perturbations such as mutations and environmental fluctuations, is pervasive in biological systems. However, robustness often coexists with its counterpart, evolvability--the ability of perturbations to generate new phenotypes. Previous models of gene regulatory network evolution have shown that robustness evolves under stabilizing selection, but it is unclear how robustness and evolvability will emerge in common coevolutionary scenarios. We consider a two-species model of coevolution involving one host and one parasite population. By using two interacting species, key model parameters that determine the fitness landscapes become emergent properties of the model, avoiding the need to impose these parameters externally. In our study, parasites are modeled on species such as cuckoos where mimicry of the host phenotype confers high fitness to the parasite but lower fitness to the host. Here, frequent phenotype changes are favored as each population continually adapts to the other population. Sensitivity evolves at the network level such that point mutations can induce large phenotype changes. Crucially, the sensitive points of the network are broadly distributed throughout the network and continually relocate. Each time sensitive points in the network are mutated, new ones appear to take their place. We have therefore named this phenomenon "whack-a-mole" sensitivity, after a popular fun park game. We predict that this type of sensitivity will evolve under conditions of strong directional selection, an observation that helps interpret existing experimental evidence, for example, during the emergence of bacterial antibiotic resistance.

  15. Systematic comparison of the response properties of protein and RNA mediated gene regulatory motifs.

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    Iyengar, Bharat Ravi; Pillai, Beena; Venkatesh, K V; Gadgil, Chetan J

    2017-05-30

    We present a framework enabling the dissection of the effects of motif structure (feedback or feedforward), the nature of the controller (RNA or protein), and the regulation mode (transcriptional, post-transcriptional or translational) on the response to a step change in the input. We have used a common model framework for gene expression where both motif structures have an activating input and repressing regulator, with the same set of parameters, to enable a comparison of the responses. We studied the global sensitivity of the system properties, such as steady-state gain, overshoot, peak time, and peak duration, to parameters. We find that, in all motifs, overshoot correlated negatively whereas peak duration varied concavely with peak time. Differences in the other system properties were found to be mainly dependent on the nature of the controller rather than the motif structure. Protein mediated motifs showed a higher degree of adaptation i.e. a tendency to return to baseline levels; in particular, feedforward motifs exhibited perfect adaptation. RNA mediated motifs had a mild regulatory effect; they also exhibited a lower peaking tendency and mean overshoot. Protein mediated feedforward motifs showed higher overshoot and lower peak time compared to the corresponding feedback motifs.

  16. Systems Genetics Analysis to Identify the Genetic Modulation of a Glaucoma-Associated Gene.

    Science.gov (United States)

    Chintalapudi, Sumana R; Jablonski, Monica M

    2017-01-01

    Loss of retinal ganglion cells (RGCs) is one of the hallmarks of retinal neurodegenerative diseases, glaucoma being one of the most common. Recently, γ-synuclein (SNCG) was shown to be highly expressed in the somas and axons of RGCs. In various mouse models of glaucoma, downregulation of Sncg gene expression correlates with RGC loss. To investigate the regulation of Sncg in RGCs, we used a systems genetics approach to identify a gene that modulates the expression of Sncg, followed by confirmatory studies in both healthy and diseased retinas. We found that chromosome 1 harbors an eQTL that modulates the expression of Sncg in the mouse retina and identified Pfdn2 as the candidate upstream modulator of Sncg expression. Downregulation of Pfdn2 in enriched RGCs causes a concomitant reduction in Sncg. In this chapter, we describe our strategy and methods for identifying and confirming a genetic modulation of a glaucoma-associated gene. A similar method can be applied to other genes expressed in other tissues.

  17. Viral RNA-Unprimed Rig-I Restrains Stat3 Activation in the Modulation of Regulatory T Cell/Th17 Cell Balance.

    Science.gov (United States)

    Yang, Hui; Guo, He-Zhou; Li, Xian-Yang; Lin, Jian; Zhang, Wu; Zhao, Jun-Mei; Zhang, Hong-Xin; Chen, Sai-Juan; Chen, Zhu; Zhu, Jiang

    2017-07-01

    Innate immunity activation by viral RNA-primed retinoid acid inducible gene-I (Rig-I) in CD4 + T cells antagonizes TGFβ signaling to suppress the differentiation of regulatory T cells (Tregs). However, how viral RNA-unliganded Rig-I (apo-Rig-I) modulates Treg generation remains unclear. In this article, we show that, in the absence of viral infection, Treg differentiation of Rig-I -/- CD4 + T cells was compromised, in the presence of increased generation of Th17 cells and overactivation of Stat3, a critical regulator tilting the Treg/Th17 cell balance. Mechanistically, apo-Rig-I physically associates with Stat3, thereby inhibiting Jak1's association with Stat3 while facilitating Shp2's association to inhibit p-Stat3 levels. Interestingly, inhibition of Stat3 ameliorates the Treg/Th17 imbalance and the colitis observed in Rig-I -/- mice. Collectively, these results uncover an independent functional contribution of the apo-Rig-I/Stat3 interaction in the maintenance of Treg/Th17 cell balance. Copyright © 2017 by The American Association of Immunologists, Inc.

  18. Modulating gradients in regulatory signals within mesenchymal stem cell seeded hydrogels: a novel strategy to engineer zonal articular cartilage.

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    Stephen D Thorpe

    Full Text Available Engineering organs and tissues with the spatial composition and organisation of their native equivalents remains a major challenge. One approach to engineer such spatial complexity is to recapitulate the gradients in regulatory signals that during development and maturation are believed to drive spatial changes in stem cell differentiation. Mesenchymal stem cell (MSC differentiation is known to be influenced by both soluble factors and mechanical cues present in the local microenvironment. The objective of this study was to engineer a cartilaginous tissue with a native zonal composition by modulating both the oxygen tension and mechanical environment thorough the depth of MSC seeded hydrogels. To this end, constructs were radially confined to half their thickness and subjected to dynamic compression (DC. Confinement reduced oxygen levels in the bottom of the construct and with the application of DC, increased strains across the top of the construct. These spatial changes correlated with increased glycosaminoglycan accumulation in the bottom of constructs, increased collagen accumulation in the top of constructs, and a suppression of hypertrophy and calcification throughout the construct. Matrix accumulation increased for higher hydrogel cell seeding densities; with DC further enhancing both glycosaminoglycan accumulation and construct stiffness. The combination of spatial confinement and DC was also found to increase proteoglycan-4 (lubricin deposition toward the top surface of these tissues. In conclusion, by modulating the environment through the depth of developing constructs, it is possible to suppress MSC endochondral progression and to engineer tissues with zonal gradients mimicking certain aspects of articular cartilage.

  19. Modulating gradients in regulatory signals within mesenchymal stem cell seeded hydrogels: a novel strategy to engineer zonal articular cartilage.

    Science.gov (United States)

    Thorpe, Stephen D; Nagel, Thomas; Carroll, Simon F; Kelly, Daniel J

    2013-01-01

    Engineering organs and tissues with the spatial composition and organisation of their native equivalents remains a major challenge. One approach to engineer such spatial complexity is to recapitulate the gradients in regulatory signals that during development and maturation are believed to drive spatial changes in stem cell differentiation. Mesenchymal stem cell (MSC) differentiation is known to be influenced by both soluble factors and mechanical cues present in the local microenvironment. The objective of this study was to engineer a cartilaginous tissue with a native zonal composition by modulating both the oxygen tension and mechanical environment thorough the depth of MSC seeded hydrogels. To this end, constructs were radially confined to half their thickness and subjected to dynamic compression (DC). Confinement reduced oxygen levels in the bottom of the construct and with the application of DC, increased strains across the top of the construct. These spatial changes correlated with increased glycosaminoglycan accumulation in the bottom of constructs, increased collagen accumulation in the top of constructs, and a suppression of hypertrophy and calcification throughout the construct. Matrix accumulation increased for higher hydrogel cell seeding densities; with DC further enhancing both glycosaminoglycan accumulation and construct stiffness. The combination of spatial confinement and DC was also found to increase proteoglycan-4 (lubricin) deposition toward the top surface of these tissues. In conclusion, by modulating the environment through the depth of developing constructs, it is possible to suppress MSC endochondral progression and to engineer tissues with zonal gradients mimicking certain aspects of articular cartilage.

  20. Identification of putative regulatory motifs in the upstream regions of co-expressed functional groups of genes in Plasmodium falciparum

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    Joshi NV

    2009-01-01

    Full Text Available Abstract Background Regulation of gene expression in Plasmodium falciparum (Pf remains poorly understood. While over half the genes are estimated to be regulated at the transcriptional level, few regulatory motifs and transcription regulators have been found. Results The study seeks to identify putative regulatory motifs in the upstream regions of 13 functional groups of genes expressed in the intraerythrocytic developmental cycle of Pf. Three motif-discovery programs were used for the purpose, and motifs were searched for only on the gene coding strand. Four motifs – the 'G-rich', the 'C-rich', the 'TGTG' and the 'CACA' motifs – were identified, and zero to all four of these occur in the 13 sets of upstream regions. The 'CACA motif' was absent in functional groups expressed during the ring to early trophozoite transition. For functional groups expressed in each transition, the motifs tended to be similar. Upstream motifs in some functional groups showed 'positional conservation' by occurring at similar positions relative to the translational start site (TLS; this increases their significance as regulatory motifs. In the ribonucleotide synthesis, mitochondrial, proteasome and organellar translation machinery genes, G-rich, C-rich, CACA and TGTG motifs, respectively, occur with striking positional conservation. In the organellar translation machinery group, G-rich motifs occur close to the TLS. The same motifs were sometimes identified for multiple functional groups; differences in location and abundance of the motifs appear to ensure different modes of action. Conclusion The identification of positionally conserved over-represented upstream motifs throws light on putative regulatory elements for transcription in Pf.

  1. The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

    Science.gov (United States)

    Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

    2016-06-01

    Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.

  2. Increased Expression and Modulated Regulatory Activity of Coinhibitory Receptors PD-1, TIGIT, and TIM-3 in Lymphocytes From Patients With Systemic Sclerosis.

    Science.gov (United States)

    Fleury, Michelle; Belkina, Anna C; Proctor, Elizabeth A; Zammitti, Christopher; Simms, Robert W; Lauffenburger, Douglas A; Snyder-Cappione, Jennifer E; Lafyatis, Robert; Dooms, Hans

    2018-04-01

    Immune dysfunction is an important component of the disease process underlying systemic sclerosis (SSc), but the mechanisms contributing to altered immune cell function in SSc remain poorly defined. This study was undertaken to measure the expression and function of the coinhibitory receptors (co-IRs) programmed cell death 1 (PD-1), T cell immunoglobulin and ITIM domain (TIGIT), T cell immunoglobulin and mucin domain 3 (TIM-3), and lymphocyte activation gene 3 (LAG-3) in lymphocyte subsets from the peripheral blood of patients with SSc. Co-IR expression levels on subsets of immune cells were analyzed using a 16-color flow cytometry panel. The functional role of co-IRs was determined by measuring cytokine production after in vitro stimulation of SSc and healthy control peripheral blood mononuclear cells (PBMCs) in the presence of co-IR-blocking antibodies. Supernatants from cultures of stimulated PBMCs were added to SSc fibroblasts, and their impact on fibroblast gene expression was measured. Mathematical modeling was used to reveal differences between co-IR functions in SSc patients and healthy controls. Levels of the co-IRs PD-1 and TIGIT were increased, and each was coexpressed, in distinct T cell subsets from SSc patients compared to healthy controls. Levels of TIM-3 were increased in SSc natural killer cells. PD-1, TIGIT, and TIM-3 antibody blockade revealed patient-specific roles of each of these co-IRs in modulating activation-induced T cell cytokine production. In contrast to healthy subjects, blockade of TIGIT and TIM-3, but not PD-1, failed to reverse inhibited cytokine production in SSc patients, indicating that enhanced T cell exhaustion is present in SSc. Finally, cytokines secreted in anti-TIM-3-treated PBMC cultures distinctly changed the gene expression profile in SSc fibroblasts. The altered expression and regulatory capacity of co-IRs in SSc lymphocytes may contribute to disease pathophysiology by modulating the cytokine-mediated cross-talk of

  3. Ex vivo modulation of the Foxo1 phosphorylation state does not lead to dysfunction of T regulatory cells.

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    Kristen Kelley Penberthy

    Full Text Available Peripheral regulatory CD4+ T cells (Treg cells prevent maladaptive inflammatory responses to innocuous foreign antigens. Treg cell dysfunction has been linked to many inflammatory diseases, including allergic airway inflammation. Glucocorticoids that are used to treat allergic airway inflammation and asthma are thought to work in part by promoting Treg cell differentiation; patients who are refractory to these drugs have defective induction of anti-inflammatory Treg cells. Previous observations suggest that Treg cells deficient in the transcription factor FoxO1 are pro-inflammatory, and that FoxO1 activity is regulated by its phosphorylation status and nuclear localization. Here, we asked whether altering the phosphorylation state of FoxO1 through modulation of a regulatory phosphatase might affect Treg cell function. In a mouse model of house dust mite-induced allergic airway inflammation, we observed robust recruitment of Treg cells to the lungs and lymph nodes of diseased mice, without an apparent increase in the Treg cytokine interleukin-10 in the airways. Intriguingly, expression of PP2A, a serine/threonine phosphatase linked to the regulation of FoxO1 phosphorylation, was decreased in the mediastinal lymph nodes of HDM-treated mice, mirroring the decreased PP2A expression seen in peripheral blood monocytes of glucocorticoid-resistant asthmatic patients. When we asked whether modulation of PP2A activity alters Treg cell function via treatment with the PP2A inhibitor okadaic acid, we observed increased phosphorylation of FoxO1 and decreased nuclear localization. However, dysregulation of FoxO1 did not impair Treg cell differentiation ex vivo or cause Treg cells to adopt a pro-inflammatory phenotype. Moreover, inhibition of PP2A activity did not affect the suppressive function of Treg cells ex vivo. Collectively, these data suggest that modulation of the phosphorylation state of FoxO1 via PP2A inhibition does not modify Treg cell function ex

  4. A distinct regulatory region of the Bmp5 locus activates gene expression following adult bone fracture or soft tissue injury.

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    Guenther, Catherine A; Wang, Zhen; Li, Emma; Tran, Misha C; Logan, Catriona Y; Nusse, Roel; Pantalena-Filho, Luiz; Yang, George P; Kingsley, David M

    2015-08-01

    Bone morphogenetic proteins (BMPs) are key signaling molecules required for normal development of bones and other tissues. Previous studies have shown that null mutations in the mouse Bmp5 gene alter the size, shape and number of multiple bone and cartilage structures during development. Bmp5 mutations also delay healing of rib fractures in adult mutants, suggesting that the same signals used to pattern embryonic bone and cartilage are also reused during skeletal regeneration and repair. Despite intense interest in BMPs as agents for stimulating bone formation in clinical applications, little is known about the regulatory elements that control developmental or injury-induced BMP expression. To compare the DNA sequences that activate gene expression during embryonic bone formation and following acute injuries in adult animals, we assayed regions surrounding the Bmp5 gene for their ability to stimulate lacZ reporter gene expression in transgenic mice. Multiple genomic fragments, distributed across the Bmp5 locus, collectively coordinate expression in discrete anatomic domains during normal development, including in embryonic ribs. In contrast, a distinct regulatory region activated expression following rib fracture in adult animals. The same injury control region triggered gene expression in mesenchymal cells following tibia fracture, in migrating keratinocytes following dorsal skin wounding, and in regenerating epithelial cells following lung injury. The Bmp5 gene thus contains an "injury response" control region that is distinct from embryonic enhancers, and that is activated by multiple types of injury in adult animals. Copyright © 2015 Elsevier Inc. All rights reserved.

  5. LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

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    Priyanka Patel

    2016-03-01

    Full Text Available A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level. Keywords: L.major, S.mansoni, Regulatory networks, Transcription factors, Database

  6. Modulation of gene expression in heart and liver of hibernating black bears (Ursus americanus).

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    Fedorov, Vadim B; Goropashnaya, Anna V; Tøien, Øivind; Stewart, Nathan C; Chang, Celia; Wang, Haifang; Yan, Jun; Showe, Louise C; Showe, Michael K; Barnes, Brian M

    2011-03-31

    Hibernation is an adaptive strategy to survive in highly seasonal or unpredictable environments. The molecular and genetic basis of hibernation physiology in mammals has only recently been studied using large scale genomic approaches. We analyzed gene expression in the American black bear, Ursus americanus, using a custom 12,800 cDNA probe microarray to detect differences in expression that occur in heart and liver during winter hibernation in comparison to summer active animals. We identified 245 genes in heart and 319 genes in liver that were differentially expressed between winter and summer. The expression of 24 genes was significantly elevated during hibernation in both heart and liver. These genes are mostly involved in lipid catabolism and protein biosynthesis and include RNA binding protein motif 3 (Rbm3), which enhances protein synthesis at mildly hypothermic temperatures. Elevated expression of protein biosynthesis genes suggests induction of translation that may be related to adaptive mechanisms reducing cardiac and muscle atrophies over extended periods of low metabolism and immobility during hibernation in bears. Coordinated reduction of transcription of genes involved in amino acid catabolism suggests redirection of amino acids from catabolic pathways to protein biosynthesis. We identify common for black bears and small mammalian hibernators transcriptional changes in the liver that include induction of genes responsible for fatty acid β oxidation and carbohydrate synthesis and depression of genes involved in lipid biosynthesis, carbohydrate catabolism, cellular respiration and detoxification pathways. Our findings show that modulation of gene expression during winter hibernation represents molecular mechanism of adaptation to extreme environments.

  7. Inference of gene regulatory networks from time series by Tsallis entropy

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    de Oliveira Evaldo A

    2011-05-01

    Full Text Available Abstract Background The inference of gene regulatory networks (GRNs from large-scale expression profiles is one of the most challenging problems of Systems Biology nowadays. Many techniques and models have been proposed for this task. However, it is not generally possible to recover the original topology with great accuracy, mainly due to the short time series data in face of the high complexity of the networks and the intrinsic noise of the expression measurements. In order to improve the accuracy of GRNs inference methods based on entropy (mutual information, a new criterion function is here proposed. Results In this paper we introduce the use of generalized entropy proposed by Tsallis, for the inference of GRNs from time series expression profiles. The inference process is based on a feature selection approach and the conditional entropy is applied as criterion function. In order to assess the proposed methodology, the algorithm is applied to recover the network topology from temporal expressions generated by an artificial gene network (AGN model as well as from the DREAM challenge. The adopted AGN is based on theoretical models of complex networks and its gene transference function is obtained from random drawing on the set of possible Boolean functions, thus creating its dynamics. On the other hand, DREAM time series data presents variation of network size and its topologies are based on real networks. The dynamics are generated by continuous differential equations with noise and perturbation. By adopting both data sources, it is possible to estimate the average quality of the inference with respect to different network topologies, transfer functions and network sizes. Conclusions A remarkable improvement of accuracy was observed in the experimental results by reducing the number of false connections in the inferred topology by the non-Shannon entropy. The obtained best free parameter of the Tsallis entropy was on average in the range 2.5

  8. Identification of a new gene regulatory circuit involving B cell receptor activated signaling using a combined analysis of experimental, clinical and global gene expression data

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    Schrader, Alexandra; Meyer, Katharina; Walther, Neele; Stolz, Ailine; Feist, Maren; Hand, Elisabeth; von Bonin, Frederike; Evers, Maurits; Kohler, Christian; Shirneshan, Katayoon; Vockerodt, Martina; Klapper, Wolfram; Szczepanowski, Monika; Murray, Paul G.; Bastians, Holger; Trümper, Lorenz; Spang, Rainer; Kube, Dieter

    2016-01-01

    To discover new regulatory pathways in B lymphoma cells, we performed a combined analysis of experimental, clinical and global gene expression data. We identified a specific cluster of genes that was coherently expressed in primary lymphoma samples and suppressed by activation of the B cell receptor (BCR) through αIgM treatment of lymphoma cells in vitro. This gene cluster, which we called BCR.1, includes numerous cell cycle regulators. A reduced expression of BCR.1 genes after BCR activation was observed in different cell lines and also in CD10+ germinal center B cells. We found that BCR activation led to a delayed entry to and progression of mitosis and defects in metaphase. Cytogenetic changes were detected upon long-term αIgM treatment. Furthermore, an inverse correlation of BCR.1 genes with c-Myc co-regulated genes in distinct groups of lymphoma patients was observed. Finally, we showed that the BCR.1 index discriminates activated B cell-like and germinal centre B cell-like diffuse large B cell lymphoma supporting the functional relevance of this new regulatory circuit and the power of guided clustering for biomarker discovery. PMID:27166259

  9. The response of early neural genes to FGF signaling or inhibition of BMP indicate the absence of a conserved neural induction module

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    Rogers Crystal D

    2011-12-01

    Full Text Available Abstract Background The molecular mechanism that initiates the formation of the vertebrate central nervous system has long been debated. Studies in Xenopus and mouse demonstrate that inhibition of BMP signaling is sufficient to induce neural tissue in explants or ES cells respectively, whereas studies in chick argue that instructive FGF signaling is also required for the expression of neural genes. Although additional signals may be involved in neural induction and patterning, here we focus on the roles of BMP inhibition and FGF8a. Results To address the question of necessity and sufficiency of BMP inhibition and FGF signaling, we compared the temporal expression of the five earliest genes expressed in the neuroectoderm and determined their requirements for induction at the onset of neural plate formation in Xenopus. Our results demonstrate that the onset and peak of expression of the genes vary and that they have different regulatory requirements and are therefore unlikely to share a conserved neural induction regulatory module. Even though all require inhibition of BMP for expression, some also require FGF signaling; expression of the early-onset pan-neural genes sox2 and foxd5α requires FGF signaling while other early genes, sox3, geminin and zicr1 are induced by BMP inhibition alone. Conclusions We demonstrate that BMP inhibition and FGF signaling induce neural genes independently of each other. Together our data indicate that although the spatiotemporal expression patterns of early neural genes are similar, the mechanisms involved in their expression are distinct and there are different signaling requirements for the expression of each gene.

  10. E3L and F1L Gene Functions Modulate the Protective Capacity of Modified Vaccinia Virus Ankara Immunization in Murine Model of Human Smallpox

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    Asisa Volz

    2018-01-01

    Full Text Available The highly attenuated Modified Vaccinia virus Ankara (MVA lacks most of the known vaccinia virus (VACV virulence and immune evasion genes. Today MVA can serve as a safety-tested next-generation smallpox vaccine. Yet, we still need to learn about regulatory gene functions preserved in the MVA genome, such as the apoptosis inhibitor genes F1L and E3L. Here, we tested MVA vaccine preparations on the basis of the deletion mutant viruses MVA-ΔF1L and MVA-ΔE3L for efficacy against ectromelia virus (ECTV challenge infections in mice. In non-permissive human tissue culture the MVA deletion mutant viruses produced reduced levels of the VACV envelope antigen B5. Upon mousepox challenge at three weeks after vaccination, MVA-ΔF1L and MVA-ΔE3L exhibited reduced protective capacity in comparison to wildtype MVA. Surprisingly, however, all vaccines proved equally protective against a lethal ECTV infection at two days after vaccination. Accordingly, the deletion mutant MVA vaccines induced high levels of virus-specific CD8+ T cells previously shown to be essential for rapidly protective MVA vaccination. These results suggest that inactivation of the anti-apoptotic genes F1L or E3L modulates the protective capacity of MVA vaccination most likely through the induction of distinct orthopoxvirus specific immunity in the absence of these viral regulatory proteins.

  11. Genetics and Molecular Biology of Epstein-Barr Virus-Encoded BART MicroRNA: A Paradigm for Viral Modulation of Host Immune Response Genes and Genome Stability

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    David H. Dreyfus

    2017-01-01

    Full Text Available Epstein-Barr virus, a ubiquitous human herpesvirus, is associated through epidemiologic evidence with common autoimmune syndromes and cancers. However, specific genetic mechanisms of pathogenesis have been difficult to identify. In this review, the author summarizes evidence that recently discovered noncoding RNAs termed microRNA encoded by Epstein-Barr virus BARF (BamHI A right frame termed BART (BamHI A right transcripts are modulators of human immune response genes and genome stability in infected and bystander cells. BART expression is apparently regulated by complex feedback loops with the host immune response regulatory NF-κB transcription factors. EBV-encoded BZLF-1 (ZEBRA protein could also regulate BART since ZEBRA contains a terminal region similar to ankyrin proteins such as IκBα that regulate host NF-κB. BALF-2 (BamHI A left frame transcript, a viral homologue of the immunoglobulin and T cell receptor gene recombinase RAG-1 (recombination-activating gene-1, may also be coregulated with BART since BALF-2 regulatory sequences are located near the BART locus. Viral-encoded microRNA and viral mRNA transferred to bystander cells through vesicles, defective viral particles, or other mechanisms suggest a new paradigm in which bystander or hit-and-run mechanisms enable the virus to transiently or chronically alter human immune response genes as well as the stability of the human genome.

  12. Modulation of human multidrug-resistance MDR-1 gene by natural curcuminoids

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    Buddhasukh Duang

    2004-04-01

    Full Text Available Abstract Background Multidrug resistance (MDR is a phenomenon that is often associated with decreased intracellular drug accumulation in patient's tumor cells resulting from enhanced drug efflux. It is related to the overexpression of a membrane protein, P-glycoprotein (Pgp-170, thereby reducing drug cytotoxicity. A variety of studies have tried to find MDR modulators which increase drug accumulation in cancer cells. Methods In this study, natural curcuminoids, pure curcumin, demethoxycurcumin and bisdemethoxycurcumin, isolated from turmeric (Curcuma longa Linn, were compared for their potential ability to modulate the human MDR-1 gene expression in multidrug resistant human cervical carcinoma cell line, KB-V1 by Western blot analysis and RT-PCR. Results Western blot analysis and RT-PCR showed that all the three curcuminoids inhibited MDR-1 gene expression, and bisdemethoxycurcumin produced maximum effect. In additional studies we found that commercial grade curcuminoid (approximately 77% curcumin, 17% demethoxycurcumin and 3% bisdemthoxycurcumin decreased MDR-1 gene expression in a dose dependent manner and had about the same potent inhibitory effect on MDR-1 gene expression as our natural curcuminoid mixtures. Conclusion These results indicate that bisdemethoxycurcumin is the most active of the curcuminoids present in turmeric for modulation of MDR-1 gene. Treatment of drug resistant KB-V1 cells with curcumin increased their sensitivity to vinblastine, which was consistent with a decreased MDR-1 gene product, a P-glycoprotein, on the cell plasma membrane. Although many drugs that prevent the P-glycoprotein function have been reported, this report describes the inhibition of MDR-1 expression by a phytochemical. The modulation of MDR-1 expression may be an attractive target for new chemosensitizing agents.

  13. Modulation of human multidrug-resistance MDR-1 gene by natural curcuminoids

    International Nuclear Information System (INIS)

    Limtrakul, Pornngarm; Anuchapreeda, Songyot; Buddhasukh, Duang

    2004-01-01

    Multidrug resistance (MDR) is a phenomenon that is often associated with decreased intracellular drug accumulation in patient's tumor cells resulting from enhanced drug efflux. It is related to the overexpression of a membrane protein, P-glycoprotein (Pgp-170), thereby reducing drug cytotoxicity. A variety of studies have tried to find MDR modulators which increase drug accumulation in cancer cells. In this study, natural curcuminoids, pure curcumin, demethoxycurcumin and bisdemethoxycurcumin, isolated from turmeric (Curcuma longa Linn), were compared for their potential ability to modulate the human MDR-1 gene expression in multidrug resistant human cervical carcinoma cell line, KB-V1 by Western blot analysis and RT-PCR. Western blot analysis and RT-PCR showed that all the three curcuminoids inhibited MDR-1 gene expression, and bisdemethoxycurcumin produced maximum effect. In additional studies we found that commercial grade curcuminoid (approximately 77% curcumin, 17% demethoxycurcumin and 3% bisdemthoxycurcumin) decreased MDR-1 gene expression in a dose dependent manner and had about the same potent inhibitory effect on MDR-1 gene expression as our natural curcuminoid mixtures. These results indicate that bisdemethoxycurcumin is the most active of the curcuminoids present in turmeric for modulation of MDR-1 gene. Treatment of drug resistant KB-V1 cells with curcumin increased their sensitivity to vinblastine, which was consistent with a decreased MDR-1 gene product, a P-glycoprotein, on the cell plasma membrane. Although many drugs that prevent the P-glycoprotein function have been reported, this report describes the inhibition of MDR-1 expression by a phytochemical. The modulation of MDR-1 expression may be an attractive target for new chemosensitizing agents

  14. Posterior association networks and functional modules inferred from rich phenotypes of gene perturbations.

    Directory of Open Access Journals (Sweden)

    Xin Wang

    Full Text Available Combinatorial gene perturbations provide rich information for a systematic exploration of genetic interactions. Despite successful applications to bacteria and yeast, the scalability of this approach remains a major challenge for higher organisms such as humans. Here, we report a novel experimental and computational framework to efficiently address this challenge by limiting the 'search space' for important genetic interactions. We propose to integrate rich phenotypes of multiple single gene perturbations to robustly predict functional modules, which can subsequently be subjected to further experimental investigations such as combinatorial gene silencing. We present posterior association networks (PANs to predict functional interactions between genes estimated using a Bayesian mixture modelling approach. The major advantage of this approach over conventional hypothesis tests is that prior knowledge can be incorporated to enhance predictive power. We demonstrate in a simulation study and on biological data, that integrating complementary information greatly improves prediction accuracy. To search for significant modules, we perform hierarchical clustering with multiscale bootstrap resampling. We demonstrate the power of the proposed methodologies in applications to Ewing's sarcoma and human adult stem cells using publicly available and custom generated data, respectively. In the former application, we identify a gene module including many confirmed and highly promising therapeutic targets. Genes in the module are also significantly overrepresented in signalling pathways that are known to be critical for proliferation of Ewing's sarcoma cells. In the latter application, we predict a functional network of chromatin factors controlling epidermal stem cell fate. Further examinations using ChIP-seq, ChIP-qPCR and RT-qPCR reveal that the basis of their genetic interactions may arise from transcriptional cross regulation. A Bioconductor package

  15. An AML1-ETO/miR-29b-1 regulatory circuit modulates phenotypic properties of acute myeloid leukemia cells.

    Science.gov (United States)

    Zaidi, Sayyed K; Perez, Andrew W; White, Elizabeth S; Lian, Jane B; Stein, Janet L; Stein, Gary S

    2017-06-20

    Acute myeloid leukemia (AML) is characterized by an aggressive clinical course and frequent cytogenetic abnormalities that include specific chromosomal translocations. The 8;21 chromosomal rearrangement disrupts the key hematopoietic RUNX1 transcription factor, and contributes to leukemia through recruitment of co-repressor complexes to RUNX1 target genes, altered subnuclear localization, and deregulation of the myeloid gene regulatory program. However, a role of non-coding microRNAs (miRs) in t(8;21)-mediated leukemogenesis is minimally understood. We present evidence of an interplay between the tumor su