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Sample records for gene regulatory modules

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

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    Hoffman Eric P

    2011-03-01

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

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

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    Yuji Zhang

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

  3. 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

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

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

    2004-02-01

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

  5. The HY5-PIF regulatory module coordinates light and temperature control of photosynthetic gene transcription.

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    Gabriela Toledo-Ortiz

    2014-06-01

    Full Text Available The ability to interpret daily and seasonal alterations in light and temperature signals is essential for plant survival. This is particularly important during seedling establishment when the phytochrome photoreceptors activate photosynthetic pigment production for photoautotrophic growth. Phytochromes accomplish this partly through the suppression of phytochrome interacting factors (PIFs, negative regulators of chlorophyll and carotenoid biosynthesis. While the bZIP transcription factor long hypocotyl 5 (HY5, a potent PIF antagonist, promotes photosynthetic pigment accumulation in response to light. Here we demonstrate that by directly targeting a common promoter cis-element (G-box, HY5 and PIFs form a dynamic activation-suppression transcriptional module responsive to light and temperature cues. This antagonistic regulatory module provides a simple, direct mechanism through which environmental change can redirect transcriptional control of genes required for photosynthesis and photoprotection. In the regulation of photopigment biosynthesis genes, HY5 and PIFs do not operate alone, but with the circadian clock. However, sudden changes in light or temperature conditions can trigger changes in HY5 and PIFs abundance that adjust the expression of common target genes to optimise photosynthetic performance and growth.

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

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

    2014-01-01

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

  7. Identification of gene co-regulatory modules and associated cis-elements involved in degenerative heart disease

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    Danko Charles G

    2009-05-01

    Full Text Available Abstract Background Cardiomyopathies, degenerative diseases of cardiac muscle, are among the leading causes of death in the developed world. Microarray studies of cardiomyopathies have identified up to several hundred genes that significantly alter their expression patterns as the disease progresses. However, the regulatory mechanisms driving these changes, in particular the networks of transcription factors involved, remain poorly understood. Our goals are (A to identify modules of co-regulated genes that undergo similar changes in expression in various types of cardiomyopathies, and (B to reveal the specific pattern of transcription factor binding sites, cis-elements, in the proximal promoter region of genes comprising such modules. Methods We analyzed 149 microarray samples from human hypertrophic and dilated cardiomyopathies of various etiologies. Hierarchical clustering and Gene Ontology annotations were applied to identify modules enriched in genes with highly correlated expression and a similar physiological function. To discover motifs that may underly changes in expression, we used the promoter regions for genes in three of the most interesting modules as input to motif discovery algorithms. The resulting motifs were used to construct a probabilistic model predictive of changes in expression across different cardiomyopathies. Results We found that three modules with the highest degree of functional enrichment contain genes involved in myocardial contraction (n = 9, energy generation (n = 20, or protein translation (n = 20. Using motif discovery tools revealed that genes in the contractile module were found to contain a TATA-box followed by a CACC-box, and are depleted in other GC-rich motifs; whereas genes in the translation module contain a pyrimidine-rich initiator, Elk-1, SP-1, and a novel motif with a GCGC core. Using a naïve Bayes classifier revealed that patterns of motifs are statistically predictive of expression patterns, with

  8. Pitx2 modulates a Tbx5-dependent gene regulatory network to maintain atrial rhythm

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    Nadadur, Rangarajan D.; Broman, Michael T.; Boukens, Bastiaan; Mazurek, Stefan R.; Yang, Xinan; van den Boogaard, Malou; Bekeny, Jenna; Gadek, Margaret; Ward, Tarsha; Zhang, Min; Qiao, Yun; Martin, James F.; Seidman, Christine E.; Seidman, Jon; Christoffels, Vincent; Efimov, Igor R.; McNally, Elizabeth M.; Weber, Christopher R.; Moskowitz, Ivan P.

    2017-01-01

    Cardiac rhythm is extremely robust, generating 2 billion contraction cycles during the average human life span. Transcriptional control of cardiac rhythm is poorly understood. We found that removal of the transcription factor gene Tbx5 from the adult mouse caused primary spontaneous and sustained atrial fibrillation (AF). Atrial cardiomyocytes from the Tbx5-mutant mice exhibited action potential abnormalities, including spontaneous depolarizations, which were rescued by chelating free calcium. We identified a multitiered transcriptional network that linked seven previously defined AF risk loci: TBX5 directly activated PITX2, and TBX5 and PITX2 antagonistically regulated membrane effector genes Scn5a, Gja1, Ryr2, Dsp, and Atp2a2. In addition, reduced Tbx5 dose by adult-specific haploinsufficiency caused decreased target gene expression, myocardial automaticity, and AF inducibility, which were all rescued by Pitx2 haploinsufficiency in mice. These results defined a transcriptional architecture for atrial rhythm control organized as an incoherent feed-forward loop, driven by TBX5 and modulated by PITX2. TBX5/PITX2 interplay provides tight control of atrial rhythm effector gene expression, and perturbation of the co-regulated network caused AF susceptibility. This work provides a model for the molecular mechanisms underpinning the genetic implication of multiple AF genome-wide association studies loci and will contribute to future efforts to stratify patients for AF risk by genotype. PMID:27582060

  9. Engineered Regulatory Systems Modulate Gene Expression of Human Commensals in the Gut.

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    Lim, Bentley; Zimmermann, Michael; Barry, Natasha A; Goodman, Andrew L

    2017-04-20

    The gut microbiota is implicated in numerous aspects of health and disease, but dissecting these connections is challenging because genetic tools for gut anaerobes are limited. Inducible promoters are particularly valuable tools because these platforms allow real-time analysis of the contribution of microbiome gene products to community assembly, host physiology, and disease. We developed a panel of tunable expression platforms for the prominent genus Bacteroides in which gene expression is controlled by a synthetic inducer. In the absence of inducer, promoter activity is fully repressed; addition of inducer rapidly increases gene expression by four to five orders of magnitude. Because the inducer is absent in mice and their diets, Bacteroides gene expression inside the gut can be modulated by providing the inducer in drinking water. We use this system to measure the dynamic relationship between commensal sialidase activity and liberation of mucosal sialic acid, a receptor and nutrient for pathogens. VIDEO ABSTRACT. Copyright © 2017 Elsevier Inc. All rights reserved.

  10. Pitx2 modulates a Tbx5-dependent gene regulatory network to maintain atrial rhythm.

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    Nadadur, Rangarajan D; Broman, Michael T; Boukens, Bastiaan; Mazurek, Stefan R; Yang, Xinan; van den Boogaard, Malou; Bekeny, Jenna; Gadek, Margaret; Ward, Tarsha; Zhang, Min; Qiao, Yun; Martin, James F; Seidman, Christine E; Seidman, Jon; Christoffels, Vincent; Efimov, Igor R; McNally, Elizabeth M; Weber, Christopher R; Moskowitz, Ivan P

    2016-08-31

    Cardiac rhythm is extremely robust, generating 2 billion contraction cycles during the average human life span. Transcriptional control of cardiac rhythm is poorly understood. We found that removal of the transcription factor gene Tbx5 from the adult mouse caused primary spontaneous and sustained atrial fibrillation (AF). Atrial cardiomyocytes from the Tbx5-mutant mice exhibited action potential abnormalities, including spontaneous depolarizations, which were rescued by chelating free calcium. We identified a multitiered transcriptional network that linked seven previously defined AF risk loci: TBX5 directly activated PITX2, and TBX5 and PITX2 antagonistically regulated membrane effector genes Scn5a, Gja1, Ryr2, Dsp, and Atp2a2 In addition, reduced Tbx5 dose by adult-specific haploinsufficiency caused decreased target gene expression, myocardial automaticity, and AF inducibility, which were all rescued by Pitx2 haploinsufficiency in mice. These results defined a transcriptional architecture for atrial rhythm control organized as an incoherent feed-forward loop, driven by TBX5 and modulated by PITX2. TBX5/PITX2 interplay provides tight control of atrial rhythm effector gene expression, and perturbation of the co-regulated network caused AF susceptibility. This work provides a model for the molecular mechanisms underpinning the genetic implication of multiple AF genome-wide association studies loci and will contribute to future efforts to stratify patients for AF risk by genotype.

  11. 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.

  12. Regulatory Snapshots: integrative mining of regulatory modules from expression time series and regulatory networks.

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    Joana P Gonçalves

    Full Text Available Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1 apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2 ignore local patterns, abundant in most interesting cases of transcriptional activity; (3 neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4 limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots. Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in

  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. Comparative Transcriptome Analysis of Genes Involved in GA-GID1-DELLA Regulatory Module in Symbiotic and Asymbiotic Seed Germination of Anoectochilus roxburghii (Wall. Lindl. (Orchidaceae

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    Si-Si Liu

    2015-12-01

    Full Text Available Anoectochilus roxburghii (Wall. Lindl. (Orchidaceae is an endangered medicinal plant in China, also called “King Medicine”. Due to lacking of sufficient nutrients in dust-like seeds, orchid species depend on mycorrhizal fungi for seed germination in the wild. As part of a conservation plan for the species, research on seed germination is necessary. However, the molecular mechanism of seed germination and underlying orchid-fungus interactions during symbiotic germination are poorly understood. In this study, Illumina HiSeq 4000 transcriptome sequencing was performed to generate a substantial sequence dataset of germinating A. roxburghii seed. A mean of 44,214,845 clean reads were obtained from each sample. 173,781 unigenes with a mean length of 653 nt were obtained. A total of 51,514 (29.64% sequences were annotated, among these, 49 unigenes encoding proteins involved in GA-GID1-DELLA regulatory module, including 31 unigenes involved in GA metabolism pathway, 5 unigenes encoding GID1, 11 unigenes for DELLA and 2 unigenes for GID2. A total of 11,881 genes showed significant differential expression in the symbiotic germinating seed sample compared with the asymbiotic germinating seed sample, of which six were involved in the GA-GID1-DELLA regulatory module, and suggested that they might be induced or suppressed by fungi. These results will help us understand better the molecular mechanism of orchid seed germination and orchid-fungus symbiosis.

  15. Comparative Transcriptome Analysis of Genes Involved in GA-GID1-DELLA Regulatory Module in Symbiotic and Asymbiotic Seed Germination of Anoectochilus roxburghii (Wall.) Lindl. (Orchidaceae).

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    Liu, Si-Si; Chen, Juan; Li, Shu-Chao; Zeng, Xu; Meng, Zhi-Xia; Guo, Shun-Xing

    2015-12-18

    Anoectochilus roxburghii (Wall.) Lindl. (Orchidaceae) is an endangered medicinal plant in China, also called "King Medicine". Due to lacking of sufficient nutrients in dust-like seeds, orchid species depend on mycorrhizal fungi for seed germination in the wild. As part of a conservation plan for the species, research on seed germination is necessary. However, the molecular mechanism of seed germination and underlying orchid-fungus interactions during symbiotic germination are poorly understood. In this study, Illumina HiSeq 4000 transcriptome sequencing was performed to generate a substantial sequence dataset of germinating A. roxburghii seed. A mean of 44,214,845 clean reads were obtained from each sample. 173,781 unigenes with a mean length of 653 nt were obtained. A total of 51,514 (29.64%) sequences were annotated, among these, 49 unigenes encoding proteins involved in GA-GID1-DELLA regulatory module, including 31 unigenes involved in GA metabolism pathway, 5 unigenes encoding GID1, 11 unigenes for DELLA and 2 unigenes for GID2. A total of 11,881 genes showed significant differential expression in the symbiotic germinating seed sample compared with the asymbiotic germinating seed sample, of which six were involved in the GA-GID1-DELLA regulatory module, and suggested that they might be induced or suppressed by fungi. These results will help us understand better the molecular mechanism of orchid seed germination and orchid-fungus symbiosis.

  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. NECK LEAF 1, a GATA type transcription factor, modulates organogenesis by regulating the expression of multiple regulatory genes during reproductive development in rice

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    Liping Wang; Hengfu Yin; Qian Qian; Jun Yang; Chaofeng Huang; Xiaohe Hu; Da Luo

    2009-01-01

    In the monocot rice species Oryza sativa L., one of the most striking morphological processes during reproductive development is the concurrence of panicle development with the sequential elongation of upper internodes (UPIs). To elucidate the underlying molecular mechanisms, we cloned the rice gene NECK LEAF 1 (NL1), which when mutated results in delays in flowering time, smaller panicles with overgrown bracts and abnormal UPI elongation patterns. The NL1 gene encodes a GATA-type transcription factor with a single zinc finger domain, and its transcripts are de-tected predominantly in the bract primordia, which normally degenerate in the wild-type plants. Overexpression of NL1 in transgenic plants often gives rise to severe growth retardation, less vegetative phytomers and smaller leaves, suggesting that NL1 plays an important role in organ differentiation. A novel mutant allele of PLASTOCHRON1 (PLA1), a gene known to play a key role in regulating leaf initiation, was identified in this study. Genetic analysis demonstrated an interaction between nll and plal, with NL1 acting upstream of PLA1. The expression level and spatial pattern of PLA1 were found to be altered in the nll mutant. Furthermore, the expression of two regulators of flowering, Hd3a and OsMADS1, was also affected in the nll mutant. On the basis of these findings, we propose that NL1 is an intrinsic factor that modulates and coordinates organogenesis through regulating the expression of PLA1 and other regulatory genes during reproductive development in rice.

  18. Idefix insulator activity can be modulated by nearby regulatory elements

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    Brasset, E; Bantignies, F.; Court, F. (Franck); Cheresiz, S.; C. Conte; Vaury, C.

    2007-01-01

    Insulators play important roles in controlling gene activity and maintaining regulatory independence between neighbouring genes. In this article, we show that the enhancer-blocking activity of the insulator present within the LTR retrotransposon Idefix can be abolished if two copies of the region containing the insulator—specifically, the long terminal repeat (LTR)—are fused to the retrotransposon's 5′ untranslated region (5′ UTR). The presence of this combination of two [LTR-5′ UTR] modules ...

  19. Analyses of fugu hoxa2 genes provide evidence for subfunctionalization of neural crest cell and rhombomere cis-regulatory modules during vertebrate evolution.

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    McEllin, Jennifer A; Alexander, Tara B; Tümpel, Stefan; Wiedemann, Leanne M; Krumlauf, Robb

    2016-01-15

    Hoxa2 gene is a primary player in regulation of craniofacial programs of head development in vertebrates. Here we investigate the evolution of a Hoxa2 neural crest enhancer identified originally in mouse by comparing and contrasting the fugu hoxa2a and hoxa2b genes with their orthologous teleost and mammalian sequences. Using sequence analyses in combination with transgenic regulatory assays in zebrafish and mouse embryos we demonstrate subfunctionalization of regulatory activity for expression in hindbrain segments and neural crest cells between these two fugu co-orthologs. hoxa2a regulatory sequences have retained the ability to mediate expression in neural crest cells while those of hoxa2b include cis-elements that direct expression in rhombomeres. Functional dissection of the neural crest regulatory potential of the fugu hoxa2a and hoxa2b genes identify the previously unknown cis-element NC5, which is implicated in generating the differential activity of the enhancers from these genes. The NC5 region plays a similar role in the ability of this enhancer to mediate reporter expression in mice, suggesting it is a conserved component involved in control of neural crest expression of Hoxa2 in vertebrate craniofacial development.

  20. Idefix insulator activity can be modulated by nearby regulatory elements.

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    Brasset, E; Bantignies, F; Court, F; Cheresiz, S; Conte, C; Vaury, C

    2007-01-01

    Insulators play important roles in controlling gene activity and maintaining regulatory independence between neighbouring genes. In this article, we show that the enhancer-blocking activity of the insulator present within the LTR retrotransposon Idefix can be abolished if two copies of the region containing the insulator--specifically, the long terminal repeat (LTR)--are fused to the retrotransposon's 5' untranslated region (5' UTR). The presence of this combination of two [LTR-5' UTR] modules is a prerequisite for the loss of enhancer-blocking activity. We further show that the 5' UTR causes flanking genomic sequences to be displaced to the nuclear periphery, which is not observed when two insulators are present by themselves. This study thus provides a functional link between insulators and independent genomic modules, which may cooperate to allow the specific regulation of defined genomic loci via nuclear repositioning. It further illustrates the complexity of genomic regulation within a chromatic environment with multiple functional elements.

  1. Modeling of hysteresis in gene regulatory networks.

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

    2012-08-01

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

  2. The Helicobacter pylori J99 jhp0106 Gene, under the Control of the CsrA/RpoN Regulatory System, Modulates Flagella Formation and Motility

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    Kao, Cheng-Yen; Chen, Jenn-Wei; Wang, Shuying; Sheu, Bor-Shyang; Wu, Jiunn-Jong

    2017-01-01

    CsrA has been shown to positively control the expression of flagella-related genes, including flaA and flaB, through regulating expression of an alternative sigma factor RpoN in Helicobacter pylori J99. Here, we aimed to characterize the CsrA regulatory system by comparative transcriptomic analysis carried out with RNA-seq on strain J99 and a csrA mutant. Fifty-three genes in the csrA mutant were found to be differentially expressed compared with the wild-type. Among CsrA-regulated genes, jhp0106, with unclear function, was found located downstream of flaB in the J99 genome. We hypothesized that flaB-jhp0106 is in an operon under the control of RpoN binding to the flaB promoter. The RT-qPCR results showed the expression of jhp0106 was decreased 76 and 92% in the csrA and rpoN mutants, respectively, compared to the wild-type. Moreover, mutations of the RpoN binding site in the flaB promoter region resulted in decreased expression of flaB and jhp0106 and deficient motility. Three-dimensional structure modeling results suggested that Jhp0106 was a glycosyltransferase. The role of jhp0106 in H. pylori was further investigated by constructing the jhp0106 mutant and revertant strains. A soft-agar motility assay and transmission electron microscope were used to determine the motility and flagellar structure of examined strains, and the results showed the loss of motility and flagellar structure in jhp0106 mutant J99. In conclusion, we found jhp0106, under the control of the CsrA/RpoN regulatory system, plays a critical role in H. pylori flagella formation.

  3. Overlapping protein-binding sites within a negative regulatory element modulate the brain-preferential expression of the human HPRT gene

    Energy Technology Data Exchange (ETDEWEB)

    Rincon-Limas, D.E.; Amaya-Manzanares, E.; Nino-Rosales, M.L. [Baylor College of Medicine, Houston, TX (United States)] [and others

    1994-09-01

    The hypoxanthine phosphoribosyltransferase (HPRT) gene, whose deficiency in humans causes the Lesch-Nyhan syndrome, is constitutively expressed at low levels in all tissues but at higher levels in the brain, the significance and mechanism of which is unknown. Towards dissecting this molecular mechanism, we have previously identified a 182 bp element (hHPRT-NE) within the 5{prime}-flanking region of the human HPRT gene which is involved not only in conferring neuronal specificity but also in repressing gene expression in non-neuronal tissues. Here we report that this element interacts with different nuclear proteins, some of which are present specifically in neuronal cells (complex I) and others of which are present in cells showing constitutive expression of the gene (complex II). In addition, we found that complex I factors are expressed in human NT2/D1 cells following induction of neuronal differentiation by retinoic acid. This finding correlates with an increase of HPRT gene transcription following neuronal differentiation, as demonstrated by RT-PCR and RNAase protection assays. We also mapped the binding sites for both complexes to a 60 bp region which, when tested by transient transfections in cultured fibroblasts, functioned as a repressor element. Methylation interference footprinting revealed a minimal unique DNA motif as the binding site for nuclear proteins from both neuronal and non-neuronal sources. Moreover, UV-crosslinking experiments showed that both complexes are formed by the association of several distinct proteins. Strikingly, site-directed mutagenesis of the footprinted region indicated that different nucleotides are essential for the association of these two complexes. These data suggest that differential formation of DNA-protein complexes at this regulatory domain could be a major determinant in the brain-preferential expression of the human HPRT gene.

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

    Directory of Open Access Journals (Sweden)

    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.

  5. A study of bacterial gene regulatory mechanisms

    DEFF Research Database (Denmark)

    Hansen, Sabine

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

  6. Inferring latent gene regulatory network kinetics

    NARCIS (Netherlands)

    González, Javier; Vujačić, Ivan; Wit, Ernst

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Hailin Chen

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

  8. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

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

    2016-11-01

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

  10. Gene regulatory mechanisms in infected fish

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  11. Oleanolic Acid Diminishes Liquid Fructose-Induced Fatty Liver in Rats: Role of Modulation of Hepatic Sterol Regulatory Element-Binding Protein-1c-Mediated Expression of Genes Responsible for De Novo Fatty Acid Synthesis

    Directory of Open Access Journals (Sweden)

    Changjin Liu

    2013-01-01

    Full Text Available Oleanolic acid (OA, contained in more than 1620 plants and as an aglycone precursor for naturally occurred and synthesized triterpenoid saponins, is used in China for liver disorders in humans. However, the underlying liver-protecting mechanisms remain largely unknown. Here, we found that treatment of rats with OA (25 mg/kg/day, gavage, once daily over 10 weeks diminished liquid fructose-induced excess hepatic triglyceride accumulation without effect on total energy intake. Attenuation of the increased vacuolization and Oil Red O staining area was evident on histological examination of liver in OA-treated rats. Hepatic gene expression profile demonstrated that OA suppressed fructose-stimulated overexpression of sterol regulatory element-binding protein-(SREBP- 1/1c mRNA and nuclear protein. In accord, overexpression of SREBP-1c-responsive genes responsible for fatty acid synthesis was also downregulated. In contrast, overexpressed nuclear protein of carbohydrate response element-binding protein and its target genes liver pyruvate kinase and microsomal triglyceride transfer protein were not altered. Additionally, OA did not affect expression of peroxisome proliferator-activated receptor-gamma- and -alpha and their target genes. It is concluded that modulation of hepatic SREBP-1c-mediated expression of the genes responsible for de novo fatty acid synthesis plays a pivotal role in OA-elicited diminishment of fructose-induced fatty liver in rats.

  12. Evolution of evolvability in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Anton Crombach

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

  13. MicroRNA and transcription factor mediated regulatory network analysis reveals critical regulators and regulatory modules in myocardial infarction.

    Directory of Open Access Journals (Sweden)

    Guangde Zhang

    Full Text Available Myocardial infarction (MI is a severe coronary artery disease and a leading cause of mortality and morbidity worldwide. However, the molecular mechanisms of MI have yet to be fully elucidated. In this study, we compiled MI-related genes, MI-related microRNAs (miRNAs and known human transcription factors (TFs, and we then identified 1,232 feed-forward loops (FFLs among these miRNAs, TFs and their co-regulated target genes through integrating target prediction. By merging these FFLs, the first miRNA and TF mediated regulatory network for MI was constructed, from which four regulators (SP1, ESR1, miR-21-5p and miR-155-5p and three regulatory modules that might play crucial roles in MI were then identified. Furthermore, based on the miRNA and TF mediated regulatory network and literature survey, we proposed a pathway model for miR-21-5p, the miR-29 family and SP1 to demonstrate their potential co-regulatory mechanisms in cardiac fibrosis, apoptosis and angiogenesis. The majority of the regulatory relations in the model were confirmed by previous studies, which demonstrated the reliability and validity of this miRNA and TF mediated regulatory network. Our study will aid in deciphering the complex regulatory mechanisms involved in MI and provide putative therapeutic targets for MI.

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

    Energy Technology Data Exchange (ETDEWEB)

    Fung, Elizabeth-sharon [Los Alamos National Laboratory

    2008-01-01

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

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

    DEFF Research Database (Denmark)

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

    2013-01-01

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

  16. Computational methods for the detection of cis-regulatory modules.

    Science.gov (United States)

    Van Loo, Peter; Marynen, Peter

    2009-09-01

    Metazoan transcription regulation occurs through the concerted action of multiple transcription factors that bind co-operatively to cis-regulatory modules (CRMs). The annotation of these key regulators of transcription is lagging far behind the annotation of the transcriptome itself. Here, we give an overview of existing computational methods to detect these CRMs in metazoan genomes. We subdivide these methods into three classes: CRM scanners screen sequences for CRMs based on predefined models that often consist of multiple position weight matrices (PWMs). CRM builders construct models of similar CRMs controlling a set of co-regulated or co-expressed genes. CRM genome screeners screen sequences or complete genomes for CRMs as homotypic or heterotypic clusters of binding sites for any combination of transcription factors. We believe that CRM scanners are currently the most advanced methods, although their applicability is limited. Finally, we argue that CRM builders that make use of PWM libraries will benefit greatly from future advances and will prove to be most instrumental for the annotation of regulatory regions in metazoan genomes.

  17. Attribute Exploration of Gene Regulatory Processes

    CERN Document Server

    Wollbold, Johannes

    2012-01-01

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

  18. Gene regulatory networks governing pancreas development.

    Science.gov (United States)

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

    2013-04-15

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

  19. 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.

  20. From elements to modules: regulatory evolution in Ascomycota fungi

    OpenAIRE

    Wohlbach, Dana J.; Thompson, Dawn Anne; Audrey P Gasch; Regev, Aviv

    2009-01-01

    Regulatory divergence is likely a major driving force in evolution. Comparative transcriptomics provides a new glimpse into the evolution of gene regulation. Ascomycota fungi are uniquely suited among eukaryotes for studies of regulatory evolution, because of broad phylogenetic scope, many sequenced genomes, and facility of genomic analysis. Here we review the substantial divergence in gene expression in Ascomycota and how this is reconciled with the modular organization of transcriptional ne...

  1. Reverse-engineering transcriptional modules from gene expression data

    OpenAIRE

    Michoel, Tom; De Smet, Riet; Joshi, Anagha; Marchal, Kathleen; de Peer, Yves Van

    2009-01-01

    "Module networks" are a framework to learn gene regulatory networks from expression data using a probabilistic model in which coregulated genes share the same parameters and conditional distributions. We present a method to infer ensembles of such networks and an averaging procedure to extract the statistically most significant modules and their regulators. We show that the inferred probabilistic models extend beyond the data set used to learn the models.

  2. 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.

  3. RNA Interference of Interferon Regulatory Factor-1 Gene Expression in THP-1 Cell Line Leads to Toll-Like Receptor-4 Overexpression/Activation As Well As Up-modulation of Annexin-II

    Directory of Open Access Journals (Sweden)

    Christos I. Maratheftis

    2007-12-01

    Full Text Available Interferon regulatory factor-1 (IRF-1 is a candidate transcription factor for the regulation of the Toll-like receptor-4 (TLR-4 gene. Using a small interfering RNAbased (siRNA process to silence IRF-1 gene expression in the leukemic monocytic cell line THP-1, we investigated whether such a modulation would alter TLR-4 expression and activation status in these cells. The siIRF-1 cells expressed elevated levels of TLR-4 mRNA and protein compared to controls by 90% and 77%, respectively. ICAM.1 protein expression and apoptosis levels were increased by 8.35- and 4.25-fold, respectively. The siIRF-1 cells overexpressed Bax mRNA compared to controls. Proteomic analysis revealed upmodulation of the Annexin-II protein in siIRF-1 THP-1 cells. Myelodysplastic syndrome (MDS patients with an absence of full-length IRF-1 mRNA also overexpressed Annexin-II. It is plausible that this overexpression may lead to the activation of TLR-4 contributing to the increased apoptosis characterizing MDS.

  4. A study of bacterial gene regulatory mechanisms

    DEFF Research Database (Denmark)

    Hansen, Sabine

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

  5. 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...

  6. Compressed Adjacency Matrices: Untangling Gene Regulatory Networks.

    Science.gov (United States)

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

    2012-12-01

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

  7. 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.

  8. Downstream Regulatory Element Antagonist Modulator (DREAM), a target for anti-thrombotic agents.

    Science.gov (United States)

    Cho, Jaehyung

    2017-03-01

    Circulating platelets participate in the process of numerous diseases including thrombosis, inflammation, and cancer. Thus, it is of great importance to understand the underlying mechanisms mediating platelet activation under disease conditions. Emerging evidence indicates that despite the lack of a nucleus, platelets possess molecules that are involved in gene transcription in nucleated cells. This review will summarize downstream regulatory element antagonist modulator (DREAM), a transcriptional repressor, and highlight recent findings suggesting its novel non-transcriptional role in hemostasis and thrombosis.

  9. A Gene Regulatory Program in Human Breast Cancer.

    Science.gov (United States)

    Li, Renhua; Campos, John; Iida, Joji

    2015-12-01

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

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

    Science.gov (United States)

    2013-01-01

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

  11. Inferring slowly-changing dynamic gene-regulatory networks

    NARCIS (Netherlands)

    Wit, Ernst C.; Abbruzzo, Antonino

    2015-01-01

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

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

    Science.gov (United States)

    Galli, Maria Cristina

    2009-11-11

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

  13. Chaotic motifs in gene regulatory networks.

    Science.gov (United States)

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

    2012-01-01

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

  14. Toward an orofacial gene regulatory network.

    Science.gov (United States)

    Kousa, Youssef A; Schutte, Brian C

    2016-03-01

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

  15. Comparative analysis of module-based versus direct methods for reverse-engineering transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Joshi Anagha

    2009-05-01

    Full Text Available Abstract Background A myriad of methods to reverse-engineer transcriptional regulatory networks have been developed in recent years. Direct methods directly reconstruct a network of pairwise regulatory interactions while module-based methods predict a set of regulators for modules of coexpressed genes treated as a single unit. To date, there has been no systematic comparison of the relative strengths and weaknesses of both types of methods. Results We have compared a recently developed module-based algorithm, LeMoNe (Learning Module Networks, to a mutual information based direct algorithm, CLR (Context Likelihood of Relatedness, using benchmark expression data and databases of known transcriptional regulatory interactions for Escherichia coli and Saccharomyces cerevisiae. A global comparison using recall versus precision curves hides the topologically distinct nature of the inferred networks and is not informative about the specific subtasks for which each method is most suited. Analysis of the degree distributions and a regulator specific comparison show that CLR is 'regulator-centric', making true predictions for a higher number of regulators, while LeMoNe is 'target-centric', recovering a higher number of known targets for fewer regulators, with limited overlap in the predicted interactions between both methods. Detailed biological examples in E. coli and S. cerevisiae are used to illustrate these differences and to prove that each method is able to infer parts of the network where the other fails. Biological validation of the inferred networks cautions against over-interpreting recall and precision values computed using incomplete reference networks. Conclusion Our results indicate that module-based and direct methods retrieve largely distinct parts of the underlying transcriptional regulatory networks. The choice of algorithm should therefore be based on the particular biological problem of interest and not on global metrics which cannot be

  16. Oct4 targets regulatory nodes to modulate stem cell function.

    Directory of Open Access Journals (Sweden)

    Pearl A Campbell

    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.

  17. Module network inference from a cancer gene expression data set identifies microRNA regulated modules.

    Directory of Open Access Journals (Sweden)

    Eric Bonnet

    Full Text Available BACKGROUND: MicroRNAs (miRNAs are small RNAs that recognize and regulate mRNA target genes. Multiple lines of evidence indicate that they are key regulators of numerous critical functions in development and disease, including cancer. However, defining the place and function of miRNAs in complex regulatory networks is not straightforward. Systems approaches, like the inference of a module network from expression data, can help to achieve this goal. METHODOLOGY/PRINCIPAL FINDINGS: During the last decade, much progress has been made in the development of robust and powerful module network inference algorithms. In this study, we analyze and assess experimentally a module network inferred from both miRNA and mRNA expression data, using our recently developed module network inference algorithm based on probabilistic optimization techniques. We show that several miRNAs are predicted as statistically significant regulators for various modules of tightly co-expressed genes. A detailed analysis of three of those modules demonstrates that the specific assignment of miRNAs is functionally coherent and supported by literature. We further designed a set of experiments to test the assignment of miR-200a as the top regulator of a small module of nine genes. The results strongly suggest that miR-200a is regulating the module genes via the transcription factor ZEB1. Interestingly, this module is most likely involved in epithelial homeostasis and its dysregulation might contribute to the malignant process in cancer cells. CONCLUSIONS/SIGNIFICANCE: Our results show that a robust module network analysis of expression data can provide novel insights of miRNA function in important cellular processes. Such a computational approach, starting from expression data alone, can be helpful in the process of identifying the function of miRNAs by suggesting modules of co-expressed genes in which they play a regulatory role. As shown in this study, those modules can then be

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

    Directory of Open Access Journals (Sweden)

    Daniel J Gaffney

    2013-05-01

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

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

    Science.gov (United States)

    Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

    2017-08-20

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

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

    Science.gov (United States)

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

    2014-04-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  2. Transcriptional Modulation of Heat-Shock Protein Gene Expression

    OpenAIRE

    Anastasis Stephanou; Latchman, David S.

    2011-01-01

    Heat-shock proteins (Hsps) are molecular chaperones that are ubiquitously expressed but are also induced in cells exposed to stressful stimuli. Hsps have been implicated in the induction and propagation of several diseases. This paper focuses on regulatory factors that control the transcription of the genes encoding Hsps. We also highlight how distinct transcription factors are able to interact and modulate Hsps in different pathological states. Thus, a better understanding of the complex sig...

  3. Transcriptional modulation of heat-shock protein gene expression.

    OpenAIRE

    A. Stephanou; Latchman, D S

    2011-01-01

    Heat-shock proteins (Hsps) are molecular chaperones that are ubiquitously expressed but are also induced in cells exposed to stressful stimuli. Hsps have been implicated in the induction and propagation of several diseases. This paper focuses on regulatory factors that control the transcription of the genes encoding Hsps. We also highlight how distinct transcription factors are able to interact and modulate Hsps in different pathological states. Thus, a better understanding of the complex sig...

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Indian Academy of Sciences (India)

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

    2013-12-01

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

  6. 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.

  7. 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

  8. Deciphering ascorbic acid regulatory pathways in ripening tomato fruit using a weighted gene correlation network analysis approach.

    Science.gov (United States)

    Gao, Chao; Ju, Zheng; Li, Shan; Zuo, Jinhua; Fu, Daqi; Tian, Huiqin; Luo, Yunbo; Zhu, Benzhong

    2013-11-01

    Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid (AsA), which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato (Solanum lycopersicum L.) fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty-four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.

  9. Deciphering Ascorbic Acid Regulatory Pathways in Ripening Tomato Fruit Using a Weighted Gene Correlation Network Analysis Approach

    Institute of Scientific and Technical Information of China (English)

    Chao Gao; Zheng Ju; Shan Li; Jinhua Zuo; Daqi Fu; Huiqin Tian; Yunbo Luo; Benzhong Zhu

    2013-01-01

    Genotype is generally determined by the co-expression of diverse genes and multiple regulatory pathways in plants. Gene co-expression analysis combining with physiological trait data provides very important information about the gene function and regulatory mechanism. L-Ascorbic acid (AsA), which is an essential nutrient component for human health and plant metabolism, plays key roles in diverse biological processes such as cell cycle, cell expansion, stress resistance, hormone synthesis, and signaling. Here, we applied a weighted gene correlation network analysis approach based on gene expression values and AsA content data in ripening tomato (Solanum lycopersicum L.) fruit with different AsA content levels, which leads to identification of AsA relevant modules and vital genes in AsA regulatory pathways. Twenty-four modules were compartmentalized according to gene expression profiling. Among these modules, one negatively related module containing genes involved in redox processes and one positively related module enriched with genes involved in AsA biosynthetic and recycling pathways were further analyzed. The present work herein indicates that redox pathways as well as hormone-signal pathways are closely correlated with AsA accumulation in ripening tomato fruit, and allowed us to prioritize candidate genes for follow-up studies to dissect this interplay at the biochemical and molecular level.

  10. Computational identification of hepatitis C virus associated microRNA-mRNA regulatory modules in human livers

    Directory of Open Access Journals (Sweden)

    Aicher Lauri D

    2009-08-01

    Full Text Available Abstract Background Hepatitis C virus (HCV is a major cause of chronic liver disease by infecting over 170 million people worldwide. Recent studies have shown that microRNAs (miRNAs, a class of small non-coding regulatory RNAs, are involved in the regulation of HCV infection, but their functions have not been systematically studied. We propose an integrative strategy for identifying the miRNA-mRNA regulatory modules that are associated with HCV infection. This strategy combines paired expression profiles of miRNAs and mRNAs and computational target predictions. A miRNA-mRNA regulatory module consists of a set of miRNAs and their targets, in which the miRNAs are predicted to coordinately regulate the level of the target mRNA. Results We simultaneously profiled the expression of cellular miRNAs and mRNAs across 30 HCV positive or negative human liver biopsy samples using microarray technology. We constructed a miRNA-mRNA regulatory network, and using a graph theoretical approach, identified 38 miRNA-mRNA regulatory modules in the network that were associated with HCV infection. We evaluated the direct miRNA regulation of the mRNA levels of targets in regulatory modules using previously published miRNA transfection data. We analyzed the functional roles of individual modules at the systems level by integrating a large-scale protein interaction network. We found that various biological processes, including some HCV infection related canonical pathways, were regulated at the miRNA level during HCV infection. Conclusion Our regulatory modules provide a framework for future experimental analyses. This report demonstrates the utility of our approach to obtain new insights into post-transcriptional gene regulation at the miRNA level in complex human diseases.

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

    Directory of Open Access Journals (Sweden)

    Kim Seon-Young

    2006-07-01

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

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

    Science.gov (United States)

    Benecke, Arndt

    2008-08-01

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

  13. 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.

  14. [Enzymatic regulatory processes in gene recombination].

    Science.gov (United States)

    Kovarskiĭ, V A; Profir, A V

    1988-01-01

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

  15. RNA sequencing of laser-capture microdissected compartments of the maize kernel identifies regulatory modules associated with endosperm cell differentiation.

    Science.gov (United States)

    Zhan, Junpeng; Thakare, Dhiraj; Ma, Chuang; Lloyd, Alan; Nixon, Neesha M; Arakaki, Angela M; Burnett, William J; Logan, Kyle O; Wang, Dongfang; Wang, Xiangfeng; Drews, Gary N; Yadegari, Ramin

    2015-03-01

    Endosperm is an absorptive structure that supports embryo development or seedling germination in angiosperms. The endosperm of cereals is a main source of food, feed, and industrial raw materials worldwide. However, the genetic networks that regulate endosperm cell differentiation remain largely unclear. As a first step toward characterizing these networks, we profiled the mRNAs in five major cell types of the differentiating endosperm and in the embryo and four maternal compartments of the maize (Zea mays) kernel. Comparisons of these mRNA populations revealed the diverged gene expression programs between filial and maternal compartments and an unexpected close correlation between embryo and the aleurone layer of endosperm. Gene coexpression network analysis identified coexpression modules associated with single or multiple kernel compartments including modules for the endosperm cell types, some of which showed enrichment of previously identified temporally activated and/or imprinted genes. Detailed analyses of a coexpression module highly correlated with the basal endosperm transfer layer (BETL) identified a regulatory module activated by MRP-1, a regulator of BETL differentiation and function. These results provide a high-resolution atlas of gene activity in the compartments of the maize kernel and help to uncover the regulatory modules associated with the differentiation of the major endosperm cell types. © 2015 American Society of Plant Biologists. All rights reserved.

  16. The identification and characterization of specific ARF-Aux/IAA regulatory modules in plant growth and development.

    Science.gov (United States)

    Krogan, Naden T; Berleth, Thomas

    2015-01-01

    The current model of auxin-inducible transcription describes numerous regulatory interactions between AUXIN RESPONSE FACTORs (ARFs) and Aux/IAAs. However, specific relationships between individual members of these families in planta remain largely uncharacterized. Using a systems biology approach, the entire suite of Aux/IAA genes directly regulated by the developmentally pivotal ARF MONOPTEROS (MP) was recently determined for multiple Arabidopsis tissue types. This study showed that MP directly targets distinct subclades of Aux/IAAs, revealing potential regulatory modules of redundantly acting Aux/IAAs involved in MP-dependent processes. Further, functional analyses indicated that the protein products of these targeted Aux/IAAs negatively feedback on MP. Thus, comprehensive identification of Aux/IAAs targeted by individual ARFs will generate biologically meaningful networks of ARF-Aux/IAA regulatory modules controlling distinct plant pathways.

  17. Gene regulatory mechanisms in infected fish

    DEFF Research Database (Denmark)

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

    2011-01-01

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

  18. Gene regulatory networks elucidating huanglongbing disease mechanisms.

    Science.gov (United States)

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

    2013-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

    LIU Bei; MENG Fanjiang; LI Yong; LIU Liyan

    2008-01-01

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

  20. Glucocorticoid receptor-dependent gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Phillip Phuc Le

    2005-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Ang Choo Y

    2010-11-01

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

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

    Science.gov (United States)

    2010-01-01

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

  3. Cohesin modulates transcription of estrogen-responsive genes.

    Science.gov (United States)

    Antony, Jisha; Dasgupta, Tanushree; Rhodes, Jenny M; McEwan, Miranda V; Print, Cristin G; O'Sullivan, Justin M; Horsfield, Julia A

    2015-03-01

    The cohesin complex has essential roles in cell division, DNA damage repair and gene transcription. The transcriptional function of cohesin is thought to derive from its ability to connect distant regulatory elements with gene promoters. Genome-wide binding of cohesin in breast cancer cells frequently coincides with estrogen receptor alpha (ER), leading to the hypothesis that cohesin facilitates estrogen-dependent gene transcription. We found that cohesin modulates the expression of only a subset of genes in the ER transcription program, either activating or repressing transcription depending on the gene target. Estrogen-responsive genes most significantly influenced by cohesin were enriched in pathways associated with breast cancer progression such as PI3K and ErbB1. In MCF7 breast cancer cells, cohesin depletion enhanced transcription of TFF1 and TFF2, and was associated with increased ER binding and increased interaction between TFF1 and its distal enhancer situated within TMPRSS3. In contrast, cohesin depletion reduced c-MYC mRNA and was accompanied by reduced interaction between a distal enhancer of c-MYC and its promoters. Our data indicates that cohesin is not a universal facilitator of ER-induced transcription and can even restrict enhancer-promoter communication. We propose that cohesin modulates transcription of estrogen-dependent genes to achieve appropriate directionality and amplitude of expression.

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

    Science.gov (United States)

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

    2013-05-01

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

  5. Discovering Study-Specific Gene Regulatory Networks

    OpenAIRE

    2014-01-01

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

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

    Science.gov (United States)

    Hinczewski, Michael; Thirumalai, D

    2016-07-01

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

  7. Conserved Cis-Regulatory Modules Control Robustness in Msx1 Expression at Single-Cell Resolution

    Science.gov (United States)

    Vance, Keith W.; Woodcock, Dan J.; Reid, John E.; Bretschneider, Till; Ott, Sascha; Koentges, Georgy

    2015-01-01

    The process of transcription is highly stochastic leading to cell-to-cell variations and noise in gene expression levels. However, key essential genes have to be precisely expressed at the correct amount and time to ensure proper cellular development and function. Studies in yeast and bacterial systems have shown that gene expression noise decreases as mean expression levels increase, a relationship that is controlled by promoter DNA sequence. However, the function of distal cis-regulatory modules (CRMs), an evolutionary novelty of metazoans, in controlling transcriptional robustness and variability is poorly understood. In this study, we used live cell imaging of transfected reporters combined with a mathematical modelling and statistical inference scheme to quantify the function of conserved Msx1 CRMs and promoters in modulating single-cell real-time transcription rates in C2C12 mouse myoblasts. The results show that the mean expression–noise relationship is solely promoter controlled for this key pluripotency regulator. In addition, we demonstrate that CRMs modulate single-cell basal promoter rate distributions in a graded manner across a population of cells. This extends the rheostatic model of CRM action to provide a more detailed understanding of CRM function at single-cell resolution. We also identify a novel CRM transcriptional filter function that acts to reduce intracellular variability in transcription rates and show that this can be phylogenetically separable from rate modulating CRM activities. These results are important for understanding how the expression of key vertebrate developmental transcription factors is precisely controlled both within and between individual cells. PMID:26342140

  8. Transcriptional Modulation of Heat-Shock Protein Gene Expression

    Directory of Open Access Journals (Sweden)

    Anastasis Stephanou

    2011-01-01

    Full Text Available Heat-shock proteins (Hsps are molecular chaperones that are ubiquitously expressed but are also induced in cells exposed to stressful stimuli. Hsps have been implicated in the induction and propagation of several diseases. This paper focuses on regulatory factors that control the transcription of the genes encoding Hsps. We also highlight how distinct transcription factors are able to interact and modulate Hsps in different pathological states. Thus, a better understanding of the complex signaling pathways regulating Hsp expression may lead to novel therapeutic targets.

  9. Transcriptional modulation of heat-shock protein gene expression.

    Science.gov (United States)

    Stephanou, Anastasis; Latchman, David S

    2011-01-01

    Heat-shock proteins (Hsps) are molecular chaperones that are ubiquitously expressed but are also induced in cells exposed to stressful stimuli. Hsps have been implicated in the induction and propagation of several diseases. This paper focuses on regulatory factors that control the transcription of the genes encoding Hsps. We also highlight how distinct transcription factors are able to interact and modulate Hsps in different pathological states. Thus, a better understanding of the complex signaling pathways regulating Hsp expression may lead to novel therapeutic targets.

  10. Prediction of Cis-Regulatory Elements Controlling Genes Differentially Expressed by Retinal and Choroidal Vascular Endothelial Cells.

    Science.gov (United States)

    Choi, Dongseok; Appukuttan, Binoy; Binek, Sierra J; Planck, Stephen R; Stout, J Timothy; Rosenbaum, James T; Smith, Justine R

    2008-01-01

    Cultured endothelial cells of the human retina and choroid demonstrate distinct patterns of gene expression. We hypothesized that differential gene expression reflected differences in the interactions of transcription factors and respective cis-regulatory motifs(s) in these two emdothelial cell subpopulations, recognizing that motifs often exist as modules. We tested this hypothesis in silico by using TRANSFAC Professional and CisModule to identify cis-regulatory motifs and modules in genes that were differentially expressed by human retinal versus choroidal endothelial cells, as identified by analysis of a microarray data set. Motifs corresponding to eight transcription factors were significantly (p < 0.05) differentially abundant in genes that were relatively highly expressed in retinal (i.e., GCCR, HMGIY, HSF1, p53, VDR) or choroidal (i.e., E2F, YY1, ZF5) endothelial cells. Predicted cis-regulatory modules were quite different for these two groups of genes. Our findings raise the possibility of exploiting specific cis-regulatory motifs to target therapy at the ocular endothelial cells subtypes responsible for neovascular age-related macular degeneration or proliferative diabetic retinopathy.

  11. 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...... beta-glucuronidase, resulting in an operon structure in which both genes are transcribed from a common promoter. We show that there is a linear correlation between the expressions of the two genes, which facilitates screening for mutants with suitable enzyme activities. In a second example, we show......, overexpression was achieved by introducing an additional gene copy into a phage attachment site on the chromosome. This resulted in a series of strains with phosphofructokinase activities from 1.4 to 11 times the wild-type activity level. In this example, the pfk gene was cloned upstream of a gusA gene encoding...

  12. Molecular characterization of a maize regulatory gene

    Energy Technology Data Exchange (ETDEWEB)

    Wessler, S.R.

    1991-12-01

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

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

    Science.gov (United States)

    Wit, Ernst C; Abbruzzo, Antonino

    2015-01-01

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

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

    Science.gov (United States)

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

    1997-12-01

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

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

    OpenAIRE

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

    1987-01-01

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

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

    OpenAIRE

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

    1987-01-01

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

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

    Science.gov (United States)

    He, Xin; Ling, Xu; Sinha, Saurabh

    2009-03-01

    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.

  18. 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.

  19. Gene Regulatory Network Reconstruction Using Conditional Mutual Information

    Directory of Open Access Journals (Sweden)

    Xiaodong Wang

    2008-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Djordje Djordjevic

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

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

    Science.gov (United States)

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

    2014-01-01

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

  2. Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation

    Science.gov (United States)

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

    2016-01-01

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

  3. Constraint and contingency in multifunctional gene regulatory circuits.

    Science.gov (United States)

    Payne, Joshua L; Wagner, Andreas

    2013-01-01

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

  4. Epigenetic Regulation of Individual Modules of the immunoglobulin heavy chain locus 3' Regulatory Region.

    Science.gov (United States)

    Birshtein, Barbara K

    2014-01-01

    The Igh locus undergoes an amazing array of DNA rearrangements and modifications during B cell development. During early stages, the variable region gene is constructed from constituent variable (V), diversity (D), and joining (J) segments (VDJ joining). B cells that successfully express an antibody can be activated, leading to somatic hypermutation (SHM) focused on the variable region, and class switch recombination (CSR), which substitutes downstream constant region genes for the originally used Cμ constant region gene. Many investigators, ourselves included, have sought to understand how these processes specifically target the Igh locus and avoid other loci and potential deleterious consequences of malignant transformation. Our laboratory has concentrated on a complex regulatory region (RR) that is located downstream of Cα, the most 3' of the Igh constant region genes. The ~40 kb 3' RR, which is predicted to serve as a downstream major regulator of the Igh locus, contains two distinct segments: an ~28 kb region comprising four enhancers, and an adjacent ~12 kb region containing multiple CTCF and Pax5 binding sites. Analysis of targeted mutations in mice by a number of investigators has concluded that the entire 3' RR enhancer region is essential for SHM and CSR (but not for VDJ joining) and for high levels of expression of multiple isotypes. The CTCF/Pax5 binding region is a candidate for influencing VDJ joining early in B cell development and serving as a potential insulator of the Igh locus. Components of the 3' RR are subject to a variety of epigenetic changes during B cell development, i.e., DNAse I hypersensitivity, histone modifications, and DNA methylation, in association with transcription factor binding. I propose that these changes provide a foundation by which regulatory elements in modules of the 3' RR function by interacting with each other and with target sequences of the Igh locus.

  5. Overview Article: Identifying transcriptional cis-regulatory modules in animal genomes

    Science.gov (United States)

    Suryamohan, Kushal; Halfon, Marc S.

    2014-01-01

    Gene expression is regulated through the activity of transcription factors and chromatin modifying proteins acting on specific DNA sequences, referred to as cis-regulatory elements. These include promoters, located at the transcription initiation sites of genes, and a variety of distal cis-regulatory modules (CRMs), the most common of which are transcriptional enhancers. Because regulated gene expression is fundamental to cell differentiation and acquisition of new cell fates, identifying, characterizing, and understanding the mechanisms of action of CRMs is critical for understanding development. CRM discovery has historically been challenging, as CRMs can be located far from the genes they regulate, have few readily-identifiable sequence characteristics, and for many years were not amenable to high-throughput discovery methods. However, the recent availability of complete genome sequences and the development of next-generation sequencing methods has led to an explosion of both computational and empirical methods for CRM discovery in model and non-model organisms alike. Experimentally, CRMs can be identified through chromatin immunoprecipitation directed against transcription factors or histone post-translational modifications, identification of nucleosome-depleted “open” chromatin regions, or sequencing-based high-throughput functional screening. Computational methods include comparative genomics, clustering of known or predicted transcription factor binding sites, and supervised machine-learning approaches trained on known CRMs. All of these methods have proven effective for CRM discovery, but each has its own considerations and limitations, and each is subject to a greater or lesser number of false-positive identifications. Experimental confirmation of predictions is essential, although shortcomings in current methods suggest that additional means of validation need to be developed. PMID:25704908

  6. Innovation of a Regulatory Mechanism Modulating Semi-determinate Stem Growth through Artificial Selection in Soybean.

    Directory of Open Access Journals (Sweden)

    Yunfeng Liu

    2016-01-01

    Full Text Available It has been demonstrated that Terminal Flowering 1 (TFL1 in Arabidopsis and its functional orthologs in other plants specify indeterminate stem growth through their specific expression that represses floral identity genes in shoot apical meristems (SAMs, and that the loss-of-function mutations at these functional counterparts result in the transition of SAMs from the vegetative to reproductive state that is essential for initiation of terminal flowering and thus formation of determinate stems. However, little is known regarding how semi-determinate stems, which produce terminal racemes similar to those observed in determinate plants, are specified in any flowering plants. Here we show that semi-determinacy in soybean is modulated by transcriptional repression of Dt1, the functional ortholog of TFL1, in SAMs. Such repression is fulfilled by recently enabled spatiotemporal expression of Dt2, an ancestral form of the APETALA1/FRUITFULL orthologs, which encodes a MADS-box factor directly binding to the regulatory sequence of Dt1. In addition, Dt2 triggers co-expression of the putative SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (GmSOC1 in SAMs, where GmSOC1 interacts with Dt2, and also directly binds to the Dt1 regulatory sequence. Heterologous expression of Dt2 and Dt1 in determinate (tfl1 Arabidopsis mutants enables creation of semi-determinacy, but the same forms of the two genes in the tfl1 and soc1 background produce indeterminate stems, suggesting that Dt2 and SOC1 both are essential for transcriptional repression of Dt1. Nevertheless, the expression of Dt2 is unable to repress TFL1 in Arabidopsis, further demonstrating the evolutionary novelty of the regulatory mechanism underlying stem growth in soybean.

  7. Spermatogenesis associated 4 promotes Sertoli cell proliferation modulated negatively by regulatory factor X1.

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    Junjun Jiang

    Full Text Available Spermatogenesis associated 4 (Spata4, a testis-specific and CpG island associated gene, is involved in regulating cell proliferation, differentiation and apoptosis. To obtain insight into the role of Spata4 in cell cycling control, we characterized the promoter region of Spata4 and investigated its transcriptional regulation mechanism. The Spata4 promoter is unidirectional transcribed and possesses multiple transcription start sites. Moreover, we present evidence that regulatory factor X1 (RFX1 could bind the typical 14-bp cis-elements of Spata4 promoter, modulate transcriptional activity and endogenous expression of Spata4, and further regulate the proliferation of Sertoli cells. Overexpression of RFX1 was shown to down-regulate both the promoter activity and mRNA expression of Spata4, whereas knockdown of RFX1 demonstrated the opposite effects. Our studies provide insight into Spata4 gene regulation and imply the potential role of RFX1 in growth of Sertoli cells. RFX1 may have negative effect on cell proliferation of Sertoli cells via modulating Spata4 expression levels by binding the conserved 14-bp cis-elements of Spata4 promoter.

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

    Directory of Open Access Journals (Sweden)

    Joy Edward Larvie

    2016-04-01

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

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

    OpenAIRE

    Frolova A. O.

    2012-01-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

  11. 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.

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

    OpenAIRE

    Qiang Zhang; Andersen, Melvin E.

    2007-01-01

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

  13. Phase transitions in the evolution of gene regulatory networks

    Science.gov (United States)

    Skanata, Antun; Kussell, Edo

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

  14. Regulatory polymorphisms modulate the expression of HLA class II molecules and promote autoimmunity

    Science.gov (United States)

    Raj, Prithvi; Rai, Ekta; Song, Ran; Khan, Shaheen; Wakeland, Benjamin E; Viswanathan, Kasthuribai; Arana, Carlos; Liang, Chaoying; Zhang, Bo; Dozmorov, Igor; Carr-Johnson, Ferdicia; Mitrovic, Mitja; Wiley, Graham B; Kelly, Jennifer A; Lauwerys, Bernard R; Olsen, Nancy J; Cotsapas, Chris; Garcia, Christine K; Wise, Carol A; Harley, John B; Nath, Swapan K; James, Judith A; Jacob, Chaim O; Tsao, Betty P; Pasare, Chandrashekhar; Karp, David R; Li, Quan Zhen; Gaffney, Patrick M; Wakeland, Edward K

    2016-01-01

    Targeted sequencing of sixteen SLE risk loci among 1349 Caucasian cases and controls produced a comprehensive dataset of the variations causing susceptibility to systemic lupus erythematosus (SLE). Two independent disease association signals in the HLA-D region identified two regulatory regions containing 3562 polymorphisms that modified thirty-seven transcription factor binding sites. These extensive functional variations are a new and potent facet of HLA polymorphism. Variations modifying the consensus binding motifs of IRF4 and CTCF in the XL9 regulatory complex modified the transcription of HLA-DRB1, HLA-DQA1 and HLA-DQB1 in a chromosome-specific manner, resulting in a 2.5-fold increase in the surface expression of HLA-DR and DQ molecules on dendritic cells with SLE risk genotypes, which increases to over 4-fold after stimulation. Similar analyses of fifteen other SLE risk loci identified 1206 functional variants tightly linked with disease-associated SNPs and demonstrated that common disease alleles contain multiple causal variants modulating multiple immune system genes. DOI: http://dx.doi.org/10.7554/eLife.12089.001 PMID:26880555

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

    Science.gov (United States)

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

    2013-12-01

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

  16. 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.

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

    Science.gov (United States)

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

    2016-08-01

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

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

    Science.gov (United States)

    Degl'Innocenti, Andrea; D'Errico, Anna

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Stefano eBerto

    2016-03-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Propagation of genetic variation in gene regulatory networks.

    Science.gov (United States)

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

    2013-08-01

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

  2. Studying the functional conservation of cis-regulatory modules and their transcriptional output

    Directory of Open Access Journals (Sweden)

    Bailey Timothy L

    2008-04-01

    Full Text Available Abstract Background Cis-regulatory modules (CRMs are distinct, genomic regions surrounding the target gene that can independently activate the promoter to drive transcription. The activation of a CRM is controlled by the binding of a certain combination of transcription factors (TFs. It would be of great benefit if the transcriptional output mediated by a specific CRM could be predicted. Of equal benefit would be identifying in silico a specific CRM as the driver of the expression in a specific tissue or situation. We extend a recently developed biochemical modeling approach to manage both prediction tasks. Given a set of TFs, their protein concentrations, and the positions and binding strengths of each of the TFs in a putative CRM, the model predicts the transcriptional output of the gene. Our approach predicts the location of the regulating CRM by using predicted TF binding sites in regions near the gene as input to the model and searching for the region that yields a predicted transcription rate most closely matching the known rate. Results Here we show the ability of the model on the example of one of the CRMs regulating the eve gene, MSE2. A model trained on the MSE2 in D. melanogaster was applied to the surrounding sequence of the eve gene in seven other Drosophila species. The model successfully predicts the correct MSE2 location and output in six out of eight Drosophila species we examine. Conclusion The model is able to generalize from D. melanogaster to other Drosophila species and accurately predicts the location and transcriptional output of MSE2 in those species. However, we also show that the current model is not specific enough to function as a genome-wide CRM scanner, because it incorrectly predicts other genomic regions to be MSE2s.

  3. Studying the functional conservation of cis-regulatory modules and their transcriptional output.

    Science.gov (United States)

    Bauer, Denis C; Bailey, Timothy L

    2008-04-29

    Cis-regulatory modules (CRMs) are distinct, genomic regions surrounding the target gene that can independently activate the promoter to drive transcription. The activation of a CRM is controlled by the binding of a certain combination of transcription factors (TFs). It would be of great benefit if the transcriptional output mediated by a specific CRM could be predicted. Of equal benefit would be identifying in silico a specific CRM as the driver of the expression in a specific tissue or situation. We extend a recently developed biochemical modeling approach to manage both prediction tasks. Given a set of TFs, their protein concentrations, and the positions and binding strengths of each of the TFs in a putative CRM, the model predicts the transcriptional output of the gene. Our approach predicts the location of the regulating CRM by using predicted TF binding sites in regions near the gene as input to the model and searching for the region that yields a predicted transcription rate most closely matching the known rate. Here we show the ability of the model on the example of one of the CRMs regulating the eve gene, MSE2. A model trained on the MSE2 in D. melanogaster was applied to the surrounding sequence of the eve gene in seven other Drosophila species. The model successfully predicts the correct MSE2 location and output in six out of eight Drosophila species we examine. The model is able to generalize from D. melanogaster to other Drosophila species and accurately predicts the location and transcriptional output of MSE2 in those species. However, we also show that the current model is not specific enough to function as a genome-wide CRM scanner, because it incorrectly predicts other genomic regions to be MSE2s.

  4. 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.

  5. Mining susceptibility gene modules and disease risk genes from SNP data by combining network topological properties with support vector regression.

    Science.gov (United States)

    Hua, Lin; Zhou, Ping; Liu, Hong; Li, Lin; Yang, Zheng; Liu, Zhi-cheng

    2011-11-21

    Genome-wide association study is a powerful approach to identify disease risk loci. However, the molecular regulatory mechanisms for most complex diseases are still not well understood. Therefore, further investigating the interplay between genetic factors and biological networks is important for elucidating the molecular mechanisms of complex diseases. Here, we proposed a novel framework to identify susceptibility gene modules and disease risk genes by combining network topological properties with support vector regression from single nucleotide polymorphism (SNP) level. We assigned risk SNPs to genes using the University of California at Santa Cruz (UCSC) genome database, and then mapped these genes to protein-protein interaction (PPI) networks. The gene modules implicated by hub genes were extracted using the PPI networks and the topological property was analyzed for these gene modules. For each gene module, risk feature genes were determined by topological property analysis and support vector regression. As a result, five shared risk feature genes, CD80, EGFR, FN1, GSK3B and TRAF6 were found and proven to be associated with rheumatoid arthritis by previous reports. Our approach showed a good performance in comparison with other approaches and can be used for prioritizing candidate genes associated with complex diseases.

  6. Topological effects of data incompleteness of gene regulatory networks

    CERN Document Server

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

    2012-01-01

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

  7. Autonomous Boolean modelling of developmental gene regulatory networks

    Science.gov (United States)

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

    2013-01-01

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

  8. Optimal finite horizon control in gene regulatory networks

    Science.gov (United States)

    Liu, Qiuli

    2013-06-01

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

  9. 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

  10. The distribution of SNPs in human gene regulatory regions

    Directory of Open Access Journals (Sweden)

    Guo Yongjian

    2005-10-01

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

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

    Science.gov (United States)

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

    2016-08-15

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

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

    Science.gov (United States)

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-09-30

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

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

    Science.gov (United States)

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

    2011-07-18

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

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Huiquan Wang

    2008-01-01

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

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

    Indian Academy of Sciences (India)

    Fathima Athar; Veena K Parnaik

    2015-09-01

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

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

    Science.gov (United States)

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

    2009-04-01

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

  18. Modulation of imprinted gene expression following superovulation.

    Science.gov (United States)

    Fortier, Amanda L; McGraw, Serge; Lopes, Flavia L; Niles, Kirsten M; Landry, Mylène; Trasler, Jacquetta M

    2014-05-05

    Although assisted reproductive technologies increase the risk of low birth weight and genomic imprinting disorders, the precise underlying causes remain unclear. Using a mouse model, we previously showed that superovulation alters the expression of imprinted genes in the placenta at 9.5days (E9.5) of gestation. Here, we investigate whether effects of superovulation on genomic imprinting persisted at later stages of development and assess the surviving fetuses for growth and morphological abnormalities. Superovulation, followed by embryo transfer at E3.5, as compared to spontaneous ovulation (controls), resulted in embryos of normal size and weight at 14.5 and 18.5days of gestation. The normal monoallelic expression of the imprinted genes H19, Snrpn and Kcnq1ot1 was unaffected in either the placentae or the embryos from the superovulated females at E14.5 or E18.5. However, for the paternally expressed imprinted gene Igf2, superovulation generated placentae with reduced production of the mature protein at E9.5 and significantly more variable mRNA levels at E14.5. We propose that superovulation results in the ovulation of abnormal oocytes with altered expression of imprinted genes, but that the coregulated genes of the imprinted gene network result in modulated expression. Copyright © 2014. Published by Elsevier Ireland Ltd.

  19. Statins as Modulators of Regulatory T-Cell Biology

    Directory of Open Access Journals (Sweden)

    David A. Forero-Peña

    2013-01-01

    Full Text Available Statins are pharmacological inhibitors of the activity of 3-hydroxy-3-methyl-glutaryl-CoA reductase (HMGCR, an enzyme responsible for the synthesis of cholesterol. Some recent experimental studies have shown that besides their effects on the primary and secondary prevention of cardiovascular diseases, statins may also have beneficial anti-inflammatory effects through diverse mechanisms. On the other hand, the induction and activity of regulatory T cells (Treg are key processes in the prevention of pathology during chronic inflammatory and autoimmune diseases. Hence, strategies oriented towards the therapeutic expansion of Tregs are gaining special attention among biomedical researchers. The potential effects of statins on the biology of Treg are of particular importance because of their eventual application as in vivo inducers of Treg in the treatment of multiple conditions. In this paper we review the experimental evidence pointing out to a potential effect of statins on the role of regulatory T cells in different conditions and discuss its potential clinical significance.

  20. The paf gene product modulates asexual development in Penicillium chrysogenum.

    Science.gov (United States)

    Hegedüs, Nikoletta; Sigl, Claudia; Zadra, Ivo; Pócsi, Istvan; Marx, Florentine

    2011-06-01

    Penicillium chrysogenum secretes a low molecular weight, cationic and cysteine-rich protein (PAF). It has growth inhibitory activity against the model organism Aspergillus nidulans and numerous zoo- and phytopathogenic fungi but shows only minimal conditional antifungal activity against the producing organism itself. In this study we provide evidence for an additional function of PAF which is distinct from the antifungal activity against putative ecologically concurrent microorganisms. Our data indicate that PAF enhances conidiation in P. chrysogenum by modulating the expression of brlA, the central regulatory gene for mitospore development. A paf deletion strain showed a significant impairment of mitospore formation which sustains our hypothesis that PAF plays an important role in balancing asexual differentiation in P. chrysogenum.

  1. Optimal Constrained Stationary Intervention in Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Golnaz Vahedi

    2008-05-01

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

  2. Optimal Constrained Stationary Intervention in Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Faryabi Babak

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2016-08-01

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

  4. The role of master regulators in gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Enrique Hernández Lemus

    2015-05-01

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

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

    Science.gov (United States)

    Marhoul, J F; Adams, T H

    1995-02-01

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

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

    Science.gov (United States)

    Hinman, Veronica F; Cheatle Jarvela, Alys M

    2014-03-01

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

  7. Toxin-mediated gene regulatory mechanism in Staphylococcus aureus

    Directory of Open Access Journals (Sweden)

    Hwang-Soo Joo

    2016-12-01

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

  8. Evolution of the mammalian embryonic pluripotency gene regulatory network

    Science.gov (United States)

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

    2010-01-01

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

  9. Global profiling of rice and poplar transcriptomes highlights key conserved circadian-controlled pathways and cis-regulatory modules.

    Directory of Open Access Journals (Sweden)

    Sergei A Filichkin

    previous findings in Arabidopsis of three major classes of cis-regulatory modules within the plant circadian network: the morning (ME, GBOX, evening (EE, GATA, and midnight (PBX/TBX/SBX modules. Identification of identical overrepresented motifs in the promoters of cycling genes from different species suggests that the core diurnal/circadian cis-regulatory network is deeply conserved between mono- and dicotyledonous species.

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

    Science.gov (United States)

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

    2016-01-01

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

  11. 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.

  12. High Dimensional ODEs Coupled with Mixed-Effects Modeling Techniques for Dynamic Gene Regulatory Network Identification.

    Science.gov (United States)

    Lu, Tao; Liang, Hua; Li, Hongzhe; Wu, Hulin

    2011-01-01

    Gene regulation is a complicated process. The interaction of many genes and their products forms an intricate biological network. Identification of this dynamic network will help us understand the biological process in a systematic way. However, the construction of such a dynamic network is very challenging for a high-dimensional system. In this article we propose to use a set of ordinary differential equations (ODE), coupled with dimensional reduction by clustering and mixed-effects modeling techniques, to model the dynamic gene regulatory network (GRN). The ODE models allow us to quantify both positive and negative gene regulations as well as feedback effects of one set of genes in a functional module on the dynamic expression changes of the genes in another functional module, which results in a directed graph network. A five-step procedure, Clustering, Smoothing, regulation Identification, parameter Estimates refining and Function enrichment analysis (CSIEF) is developed to identify the ODE-based dynamic GRN. In the proposed CSIEF procedure, a series of cutting-edge statistical methods and techniques are employed, that include non-parametric mixed-effects models with a mixture distribution for clustering, nonparametric mixed-effects smoothing-based methods for ODE models, the smoothly clipped absolute deviation (SCAD)-based variable selection, and stochastic approximation EM (SAEM) approach for mixed-effects ODE model parameter estimation. The key step, the SCAD-based variable selection of the proposed procedure is justified by investigating its asymptotic properties and validated by Monte Carlo simulations. We apply the proposed method to identify the dynamic GRN for yeast cell cycle progression data. We are able to annotate the identified modules through function enrichment analyses. Some interesting biological findings are discussed. The proposed procedure is a promising tool for constructing a general dynamic GRN and more complicated dynamic networks.

  13. cis-Regulatory control of the initial neurogenic pattern of onecut gene expression in the sea urchin embryo.

    Science.gov (United States)

    Barsi, Julius C; Davidson, Eric H

    2016-01-01

    Specification of the ciliated band (CB) of echinoid embryos executes three spatial functions essential for postgastrular organization. These are establishment of a band about 5 cells wide which delimits and bounds other embryonic territories; definition of a neurogenic domain within this band; and generation within it of arrays of ciliary cells that bear the special long cilia from which the structure derives its name. In Strongylocentrotus purpuratus the spatial coordinates of the future ciliated band are initially and exactly determined by the disposition of a ring of cells that transcriptionally activate the onecut homeodomain regulatory gene, beginning in blastula stage, long before the appearance of the CB per se. Thus the cis-regulatory apparatus that governs onecut expression in the blastula directly reveals the genomic sequence code by which these aspects of the spatial organization of the embryo are initially determined. We screened the entire onecut locus and its flanking region for transcriptionally active cis-regulatory elements, and by means of BAC recombineered deletions identified three separated and required cis-regulatory modules that execute different functions. The operating logic of the crucial spatial control module accounting for the spectacularly precise and beautiful early onecut expression domain depends on spatial repression. Previously predicted oral ectoderm and aboral ectoderm repressors were identified by cis-regulatory mutation as the products of goosecoid and irxa genes respectively, while the pan-ectodermal activator SoxB1 supplies a transcriptional driver function.

  14. The microRNA (miRNA): overview of the RNA genes that modulate gene function.

    Science.gov (United States)

    Ying, Shao-Yao; Chang, Donald C; Lin, Shi-Lung

    2008-03-01

    MicroRNAs (miRNAs), widely distributed, small regulatory RNA genes, target both messenger RNA (mRNA) degradation and suppression of protein translation based on sequence complementarity between the miRNA and its targeted mRNA. Different names have been used to describe various types of miRNA. During evolution, RNA retroviruses or transgenes invaded the eukaryotic genome and inserted in the non-coding regions of DNA, conceivably acting as transposon-like jumping genes, providing defense from viral invasion and fine-tuning of gene expression as a secondary level of gene modulation in eukaryotes. When a transposon is inserted in the intron, it becomes an intronic miRNA, taking advantage of the protein synthesis machinery, i.e., mRNA transcription and splicing, as a means for processing and maturation. Recently, miRNAs have been found to play an important, but not life-threatening, role in embryonic development. They might play a pivotal role in diverse biological systems in various organisms, facilitating a quick response and accurate plotting of body physiology and structures. Based on these unique properties, man-made intronic miRNAs have been developed for in vitro evaluation of gene function, in vivo gene therapy and generation of transgenic animal models. The biogenesis and identification of miRNAs, potential applications, and future directions for research are presented, hopefully providing a guideline for further miRNA and gene function studies.

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

    DEFF Research Database (Denmark)

    Wong, Wendy S W; Nielsen, Rasmus

    2007-01-01

    of the increasing availability of comparative genomic data. RESULTS: We develop a method for finding regulatory modules in Eukaryotic species using phylogenetic data. Using computer simulations and analysis of real data, we show that the use of phylogenetic hidden Markov model can lead to an increase in accuracy...

  16. 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.

  17. 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.

  18. 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.

  19. SMCis: An Effective Algorithm for Discovery of Cis-Regulatory Modules

    Science.gov (United States)

    Guo, Haitao; Huo, Hongwei; Yu, Qiang

    2016-01-01

    The discovery of cis-regulatory modules (CRMs) is a challenging problem in computational biology. Limited by the difficulty of using an HMM to model dependent features in transcriptional regulatory sequences (TRSs), the probabilistic modeling methods based on HMMs cannot accurately represent the distance between regulatory elements in TRSs and are cumbersome to model the prevailing dependencies between motifs within CRMs. We propose a probabilistic modeling algorithm called SMCis, which builds a more powerful CRM discovery model based on a hidden semi-Markov model. Our model characterizes the regulatory structure of CRMs and effectively models dependencies between motifs at a higher level of abstraction based on segments rather than nucleotides. Experimental results on three benchmark datasets indicate that our method performs better than the compared algorithms. PMID:27637070

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Mario Pujato

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

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

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    Aditya J Sethi

    2009-02-01

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

  3. 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.

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

    Science.gov (United States)

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

    2017-01-01

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

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

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    Arun Krishnan

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ricardo Pinho

    2014-11-01

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

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

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    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.

  9. Gene-Regulatory Activity of α-Tocopherol

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    John K. Lodge

    2010-03-01

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

  10. Modeling gene regulatory networks: A network simplification algorithm

    Science.gov (United States)

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

    2016-12-01

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

  11. 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.

  12. Validation of Gene Regulatory Network Inference Based on Controllability

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    Edward eDougherty

    2013-12-01

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

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

    Science.gov (United States)

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

    2016-09-01

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

  14. Inferring polymorphism-induced regulatory gene networks active in human lymphocyte cell lines by weighted linear mixed model analysis of multiple RNA-Seq datasets.

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    Wensheng Zhang

    Full Text Available Single-nucleotide polymorphisms (SNPs contribute to the between-individual expression variation of many genes. A regulatory (trait-associated SNP is usually located near or within a (host gene, possibly influencing the gene's transcription or/and post-transcriptional modification. But its targets may also include genes that are physically farther away from it. A heuristic explanation of such multiple-target interferences is that the host gene transfers the SNP genotypic effects to the distant gene(s by a transcriptional or signaling cascade. These connections between the host genes (regulators and the distant genes (targets make the genetic analysis of gene expression traits a promising approach for identifying unknown regulatory relationships. In this study, through a mixed model analysis of multi-source digital expression profiling for 140 human lymphocyte cell lines (LCLs and the genotypes distributed by the international HapMap project, we identified 45 thousands of potential SNP-induced regulatory relationships among genes (the significance level for the underlying associations between expression traits and SNP genotypes was set at FDR < 0.01. We grouped the identified relationships into four classes (paradigms according to the two different mechanisms by which the regulatory SNPs affect their cis- and trans- regulated genes, modifying mRNA level or altering transcript splicing patterns. We further organized the relationships in each class into a set of network modules with the cis- regulated genes as hubs. We found that the target genes in a network module were often characterized by significant functional similarity, and the distributions of the target genes in three out of the four networks roughly resemble a power-law, a typical pattern of gene networks obtained from mutation experiments. By two case studies, we also demonstrated that significant biological insights can be inferred from the identified network modules.

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

    Science.gov (United States)

    Martyanov, Viktor; Gross, Robert H

    2011-05-31

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

  16. Evolution of the CNS myelin gene regulatory program.

    Science.gov (United States)

    Li, Huiliang; Richardson, William D

    2016-06-15

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

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

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yongxin Tao

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

  19. Statistical inference of transcriptional module-based gene networks from time course gene expression profiles by using state space models.

    Science.gov (United States)

    Hirose, Osamu; Yoshida, Ryo; Imoto, Seiya; Yamaguchi, Rui; Higuchi, Tomoyuki; Charnock-Jones, D Stephen; Print, Cristin; Miyano, Satoru

    2008-04-01

    Statistical inference of gene networks by using time-course microarray gene expression profiles is an essential step towards understanding the temporal structure of gene regulatory mechanisms. Unfortunately, most of the current studies have been limited to analysing a small number of genes because the length of time-course gene expression profiles is fairly short. One promising approach to overcome such a limitation is to infer gene networks by exploring the potential transcriptional modules which are sets of genes sharing a common function or involved in the same pathway. In this article, we present a novel approach based on the state space model to identify the transcriptional modules and module-based gene networks simultaneously. The state space model has the potential to infer large-scale gene networks, e.g. of order 10(3), from time-course gene expression profiles. Particularly, we succeeded in the identification of a cell cycle system by using the gene expression profiles of Saccharomyces cerevisiae in which the length of the time-course and number of genes were 24 and 4382, respectively. However, when analysing shorter time-course data, e.g. of length 10 or less, the parameter estimations of the state space model often fail due to overfitting. To extend the applicability of the state space model, we provide an approach to use the technical replicates of gene expression profiles, which are often measured in duplicate or triplicate. The use of technical replicates is important for achieving highly-efficient inferences of gene networks with short time-course data. The potential of the proposed method has been demonstrated through the time-course analysis of the gene expression profiles of human umbilical vein endothelial cells (HUVECs) undergoing growth factor deprivation-induced apoptosis. Supplementary Information and the software (TRANS-MNET) are available at http://daweb.ism.ac.jp/~yoshidar/software/ssm/.

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

    Science.gov (United States)

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

    2015-09-01

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

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

    Science.gov (United States)

    Tan, Mehmet; Alhajj, Reda; Polat, Faruk

    2010-04-01

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

  2. 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

  3. 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.

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

    OpenAIRE

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

    2007-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

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

    Science.gov (United States)

    Cunha, Paulo M F; Sandmann, Thomas; Gustafson, E Hilary; Ciglar, Lucia; Eichenlaub, Michael P; Furlong, Eileen E M

    2010-07-01

    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.

  7. 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.

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

    NARCIS (Netherlands)

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

    2010-01-01

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

  9. 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.

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    Philip Cowie

    2013-01-01

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

  12. Regulatory elements of Caenorhabditis elegans ribosomal protein genes

    Directory of Open Access Journals (Sweden)

    Sleumer Monica C

    2012-08-01

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

  13. 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

  14. Mode of Delivery Shapes Gut Colonization Pattern and Modulates Regulatory Immunity in Mice

    DEFF Research Database (Denmark)

    H. F. Hansen, Camilla; S. F. Andersen, Line; Krych, Łukasz

    2014-01-01

    Delivery mode has been associated with long-term changes in gut microbiota composition and more recently also with changes in the immune system. This has further been suggested to link Cesarean section (C-section) with an increased risk for development of immune-mediated diseases such as type 1...... 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....

  15. Regulatory T-cells have a prominent role in the immune modulated vaccine response by specific oligosaccharides

    NARCIS (Netherlands)

    van't Land, Belinda; Schijf, Marcel; van Esch, Betty C. A. M.; van Bergenhenegouwen, Jeroen; Bastiaans, Jacqueline; Schouten, Bastiaan; Boon, Louis; Garssen, Johan

    2010-01-01

    Regulatory T-cells are increasingly important in vaccine strategies. In a Flu-vaccination model the role of CD4(+)CD25(+)Foxp3(+) regulatory T-cells (Tregs) and the immune modulation by orally supplied prebiotic oligosaccharides consisting of scGOS/lcFOS/pAOS, were assessed using anti-CD25 (PC61) me

  16. 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.

  17. Epigenetic regulation of individual modules of the immunoglobulin heavy chain locus 3’ regulatory region (3’ RR

    Directory of Open Access Journals (Sweden)

    Barbara K Birshtein

    2014-04-01

    Full Text Available The Igh locus undergoes an amazing array of DNA rearrangements and modifications during B cell development. During early stages, the variable region gene is constructed from constituent variable (V, diversity (D and joining (J segments (VDJ joining. B cells that successfully express an antibody can be activated, leading to somatic hypermutation (SHM focused on the variable region, and class switch recombination (CSR, which substitutes downstream constant region genes for the originally used Cμ constant region gene. Many investigators, ourselves included, have sought to understand how these processes specifically target the Igh locus and avoid other loci and potential deleterious consequences of malignant transformation. Our laboratory has concentrated on a complex regulatory region (RR that is located downstream of Cα, the most 3’ of the Igh constant region genes. The ~40 kb 3’ RR, which is predicted to serve as a downstream major regulator of the Igh locus, contains two distinct segments: an ~28 kb region of four enhancers and an adjacent ~12 kb region containing multiple CTCF and Pax5 binding sites. Analysis of targeted mutations in mice by a number of investigators has concluded that the entire 3’ RR enhancer region is essential for SHM and CSR (but not for VDJ joining and for high levels of expression of multiple isotypes. The CTCF/Pax5 binding region is a candidate for influencing VDJ joining early in B cell development and serving as a potential insulator of the Igh locus. Components of the 3’ RR are subject to a variety of epigenetic changes during B cell development, i.e., DNAse I hypersensitivity, histone modifications and DNA methylation, in association with transcription factor binding. We propose that these changes provide a foundation by which regulatory elements in modules of the 3’ RR function by interacting with each other and with target sequences of the Igh locus.

  18. 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

  19. A modulated empirical Bayes model for identifying topological and temporal estrogen receptor α regulatory networks in breast cancer

    Directory of Open Access Journals (Sweden)

    Zhao Yuming

    2011-05-01

    Full Text Available Abstract Background Estrogens regulate diverse physiological processes in various tissues through genomic and non-genomic mechanisms that result in activation or repression of gene expression. Transcription regulation upon estrogen stimulation is a critical biological process underlying the onset and progress of the majority of breast cancer. Dynamic gene expression changes have been shown to characterize the breast cancer cell response to estrogens, the every molecular mechanism of which is still not well understood. Results We developed a modulated empirical Bayes model, and constructed a novel topological and temporal transcription factor (TF regulatory network in MCF7 breast cancer cell line upon stimulation by 17β-estradiol stimulation. In the network, significant TF genomic hubs were identified including ER-alpha and AP-1; significant non-genomic hubs include ZFP161, TFDP1, NRF1, TFAP2A, EGR1, E2F1, and PITX2. Although the early and late networks were distinct ( Conclusions We identified a number of estrogen regulated target genes and established estrogen-regulated network that distinguishes the genomic and non-genomic actions of estrogen receptor. Many gene targets of this network were not active anymore in anti-estrogen resistant cell lines, possibly because their DNA methylation and histone acetylation patterns have changed.

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

    Directory of Open Access Journals (Sweden)

    Frolova A. O.

    2012-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Bernhard Steiert

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

  2. Modulating gene function with peptide nucleic acids (PNA)

    DEFF Research Database (Denmark)

    Nielsen, Peter E.; Crooke, Stanley T.

    2008-01-01

    A review on peptide nucleic acid (PNA) oligomers as modulators of gene expression ranging from gene silencing at the mRNAor the dsDNA (antigene) level, and redirection of mRNA splicing to gene activation through transcription bubble mimicking. PNA chem., anti-infective agents, cellular delivery, ...

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

    Science.gov (United States)

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

    2011-10-01

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

  4. Composition and abstraction of logical regulatory modules: application to multicellular systems.

    Science.gov (United States)

    Mendes, Nuno D; Lang, Frédéric; Le Cornec, Yves-Stan; Mateescu, Radu; Batt, Gregory; Chaouiya, Claudine

    2013-03-15

    Logical (Boolean or multi-valued) modelling is widely used to study regulatory or signalling networks. Even though these discrete models constitute a coarse, yet useful, abstraction of reality, the analysis of large networks faces a classical combinatorial problem. Here, we propose to take advantage of the intrinsic modularity of inter-cellular networks to set up a compositional procedure that enables a significant reduction of the dynamics, yet preserving the reachability of stable states. To that end, we rely on process algebras, a well-established computational technique for the specification and verification of interacting systems. We develop a novel compositional approach to support the logical modelling of interconnected cellular networks. First, we formalize the concept of logical regulatory modules and their composition. Then, we make this framework operational by transposing the composition of logical modules into a process algebra framework. Importantly, the combination of incremental composition, abstraction and minimization using an appropriate equivalence relation (here the safety equivalence) yields huge reductions of the dynamics. We illustrate the potential of this approach with two case-studies: the Segment-Polarity and the Delta-Notch modules.

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

    NARCIS (Netherlands)

    Roelvink, P.W.

    1989-01-01

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

  6. 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…

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

    Directory of Open Access Journals (Sweden)

    Ivan Moszer

    2006-04-01

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

  8. Identifying disease feature genes based on cellular localized gene functional modules and regulation networks

    Institute of Scientific and Technical Information of China (English)

    ZHANG Min; ZHU Jing; GUO Zheng; LI Xia; YANG Da; WANG Lei; RAO Shaoqi

    2006-01-01

    Identifying disease-relevant genes and functional modules, based on gene expression profiles and gene functional knowledge, is of high importance for studying disease mechanisms and subtyping disease phenotypes. Using gene categories of biological process and cellular component in Gene Ontology, we propose an approach to selecting functional modules enriched with differentially expressed genes, and identifying the feature functional modules of high disease discriminating abilities. Using the differentially expressed genes in each feature module as the feature genes, we reveal the relevance of the modules to the studied diseases. Using three datasets for prostate cancer, gastric cancer, and leukemia, we have demonstrated that the proposed modular approach is of high power in identifying functionally integrated feature gene subsets that are highly relevant to the disease mechanisms. Our analysis has also shown that the critical disease-relevant genes might be better recognized from the gene regulation network, which is constructed using the characterized functional modules, giving important clues to the concerted mechanisms of the modules responding to complex disease states. In addition, the proposed approach to selecting the disease-relevant genes by jointly considering the gene functional knowledge suggests a new way for precisely classifying disease samples with clear biological interpretations, which is critical for the clinical diagnosis and the elucidation of the pathogenic basis of complex diseases.

  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.

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

    Science.gov (United States)

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

    2016-02-11

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

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

    Science.gov (United States)

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

    2002-01-01

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

  12. 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.

  13. Robust dynamic balance of AP-1 transcription factors in a neuronal gene regulatory network

    Directory of Open Access Journals (Sweden)

    Schwaber James S

    2010-12-01

    Full Text Available Abstract Background The octapeptide Angiotensin II is a key hormone that acts via its receptor AT1R in the brainstem to modulate the blood pressure control circuits and thus plays a central role in the cardiac and respiratory homeostasis. This modulation occurs via activation of a complex network of signaling proteins and transcription factors, leading to changes in levels of key genes and proteins. AT1R initiated activity in the nucleus tractus solitarius (NTS, which regulates blood pressure, has been the subject of extensive molecular analysis. But the adaptive network interactions in the NTS response to AT1R, plausibly related to the development of hypertension, are not understood. Results We developed and analyzed a mathematical model of AT1R-activated signaling kinases and a downstream gene regulatory network, with structural basis in our transcriptomic data analysis and literature. To our knowledge, our report presents the first computational model of this key regulatory network. Our simulations and analysis reveal a dynamic balance among distinct dimers of the AP-1 family of transcription factors. We investigated the robustness of this behavior to simultaneous perturbations in the network parameters using a novel multivariate approach that integrates global sensitivity analysis with decision-tree methods. Our analysis implicates a subset of Fos and Jun dependent mechanisms, with dynamic sensitivities shifting from Fos-regulating kinase (FRK-mediated processes to those downstream of c-Jun N-terminal kinase (JNK. Decision-tree analysis indicated that while there may be a large combinatorial functional space feasible for neuronal states and parameters, the network behavior is constrained to a small set of AP-1 response profiles. Many of the paths through the combinatorial parameter space lead to a dynamic balance of AP-1 dimer forms, yielding a robust AP-1 response counteracting the biological variability. Conclusions Based on the simulation

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

    OpenAIRE

    Paulevé, Loïc; Magnin, Morgan; Roux, Olivier

    2011-01-01

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

  15. 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.

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

    Directory of Open Access Journals (Sweden)

    Zhu Yunping

    2010-12-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Science.gov (United States)

    Sparks, Erin E; Benfey, Philip N

    2016-01-01

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

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

    Science.gov (United States)

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

    2013-02-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-03-18

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

  2. Dynamic control of the complement system by modulated expression of regulatory proteins.

    Science.gov (United States)

    Thurman, Joshua M; Renner, Brandon

    2011-01-01

    The complement system serves many biological functions, including the eradication of invasive pathogens and the removal of damaged cells and immune-complexes. Uncontrolled complement activation causes injury to host cells, however, so adequate regulation of the system is essential. Control of the complement system is maintained by a group of cell surface and circulating proteins referred to as complement regulatory proteins. The expression of the cell surface complement regulatory proteins varies from tissue to tissue. Furthermore, specific cell types can upregulate or downregulate the expression of these proteins in response to a variety of signals or insults. Altered regulation of the complement regulatory proteins can have important effects on local complement activation. In some circumstances this can be beneficial, such as in the setting of certain infections. In other circumstances, however, this can be a cause of complement-mediated injury of the tissue. A full understanding of the mechanisms by which the complement system is modulated at the local level can have important implications for how we diagnose and treat a wide range of inflammatory diseases.

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  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

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

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

    Directory of Open Access Journals (Sweden)

    Franziska Herrmann

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

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

    Science.gov (United States)

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

    2012-01-01

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

  7. 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

    2017-07-31

    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.

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

    Science.gov (United States)

    Kim, Haseong; Gelenbe, Erol

    2012-09-01

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

  9. Differential regulation of horizontally acquired and core genome genes by the bacterial modulator H-NS.

    Directory of Open Access Journals (Sweden)

    Rosa C Baños

    2009-06-01

    Full Text Available Horizontal acquisition of DNA by bacteria dramatically increases genetic diversity and hence successful bacterial colonization of several niches, including the human host. A relevant issue is how this newly acquired DNA interacts and integrates in the regulatory networks of the bacterial cell. The global modulator H-NS targets both core genome and HGT genes and silences gene expression in response to external stimuli such as osmolarity and temperature. Here we provide evidence that H-NS discriminates and differentially modulates core and HGT DNA. As an example of this, plasmid R27-encoded H-NS protein has evolved to selectively silence HGT genes and does not interfere with core genome regulation. In turn, differential regulation of both gene lineages by resident chromosomal H-NS requires a helper protein: the Hha protein. Tight silencing of HGT DNA is accomplished by H-NS-Hha complexes. In contrast, core genes are modulated by H-NS homoligomers. Remarkably, the presence of Hha-like proteins is restricted to the Enterobacteriaceae. In addition, conjugative plasmids encoding H-NS variants have hitherto been isolated only from members of the family. Thus, the H-NS system in enteric bacteria presents unique evolutionary features. The capacity to selectively discriminate between core and HGT DNA may help to maintain horizontally transmitted DNA in silent form and may give these bacteria a competitive advantage in adapting to new environments, including host colonization.

  10. Using BAC transgenesis in zebrafish to identify regulatory sequences of the amyloid precursor protein gene in humans

    Directory of Open Access Journals (Sweden)

    Shakes Leighcraft A

    2012-09-01

    factors. Conclusion The results suggest that the clock-regulated and immune system modulator transcription factor E4BP4/ NFIL3 likely regulates the expression of both appb in zebrafish and APP in humans. It suggests potential human APP gene regulatory pathways, not on the basis of comparing DNA primary sequences with zebrafish appb but on the model of conservation of transcription factors.

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

    Directory of Open Access Journals (Sweden)

    Baumbach Jan

    2007-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Fu-Liu Casey S

    2007-05-01

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

  13. Niche-modulated and niche-modulating genes in bone marrow cells

    Science.gov (United States)

    Cohen, Y; Garach-Jehoshua, O; Bar-Chaim, A; Kornberg, A

    2012-01-01

    Bone marrow (BM) cells depend on their niche for growth and survival. However, the genes modulated by niche stimuli have not been discriminated yet. For this purpose, we investigated BM aspirations from patients with various hematological malignancies. Each aspirate was fractionated, and the various samples were fixed at different time points and analyzed by microarray. Identification of niche-modulated genes relied on sustained change in expression following loss of niche regulation. Compared with the reference (‘authentic') samples, which were fixed immediately following aspiration, the BM samples fixed after longer stay out-of-niche acquired numerous changes in gene-expression profile (GEP). The overall genes modulated included a common subset of functionally diverse genes displaying prompt and sustained ‘switch' in expression irrespective of the tumor type. Interestingly, the ‘switch' in GEP was reversible and turned ‘off-and-on' again in culture conditions, resuming cell–cell–matrix contact versus respread into suspension, respectively. Moreover, the resuming of contact prolonged the survival of tumor cells out-of-niche, and the regression of the ‘contactless switch' was followed by induction of a new set of genes, this time mainly encoding extracellular proteins including angiogenic factors and extracellular matrix proteins. Our data set, being unique in authentic expression design, uncovered niche-modulated and niche-modulating genes capable of controlling homing, expansion and angiogenesis. PMID:23241658

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

    Science.gov (United States)

    Ueki, Toshiyuki; Lovley, Derek R

    2010-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Jennifer Ferguson

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

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

    Science.gov (United States)

    Ferguson, Jennifer; Gomes, Suzanne; Civetta, Alberto

    2013-01-01

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Bor-Sen Chen

    2010-05-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2011-01-01

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

  1. Phosphatidylinositol 3-kinase p85 regulatory subunit gene and spinal muscular atrophy disease

    Directory of Open Access Journals (Sweden)

    Monica STAVARACHI

    2009-11-01

    Full Text Available Spinal muscular atrophy (SMA is a frequent neuromuscular disorder caused by motoneuronal apoptosis, as a result of SMN (Survival Motor Neuron protein deficiency. Although the SMA determining gene was identified, the molecular mechanism of the disease is not clearly understood, due to the heterogeneity of clinical manifestations. Trying to complete the molecular describing SMA picture, by identifying potential modulators factors, we investigated the relationship between phosphatidylinositol 3-kinase p85 regulatory subunit gene (PIK3R1 and SMA pathology. As IGF signaling pathway has been reported to play an important role in motoneurons survival and PIK3 is a key element of this cascade signaling, we focused on the relationship between PIK3R1 gene Met326Ile polymorphism and SMA type I, the most severe form of the disease. A total of 80 subjects (40 SMA type I patients and 40 unrelated healthy controls were included in the study. The statistical analyzes performed consequently to the genotyping by mismatch PCR-RFLP method, revealed that Met326Ile polymorphism is not associated with SMA type I disease: ORMet/Met = 0.398 with a p = 0.072 meanwhile ORMet = 0.495, p = 0.063. However, the Cochrane – Armitage test indicated that there is a statistically association trend between the analyzed polymorphism and SMA type I pathology: ORMet = 0.438, p = 0.032. We concluded that additional researches with an increased subjects number and replicates studies in other populations will clarify the investigated relationship and it may contribute to the SMA molecular mechanism understanding.

  2. A meta-analysis of caloric restriction gene expression profiles to infer common signatures and regulatory mechanisms.

    Science.gov (United States)

    Plank, Michael; Wuttke, Daniel; van Dam, Sipko; Clarke, Susan A; de Magalhães, João Pedro

    2012-04-01

    Caloric restriction, a reduction in calorie intake without malnutrition, retards age-related degeneration and extends lifespan in several organisms. CR induces multiple changes, yet its underlying mechanisms remain poorly understood. In this work, we first performed a meta-analysis of microarray CR studies in mammals and identified genes and processes robustly altered due to CR. Our results reveal a complex array of CR-induced changes and we re-identified several genes and processes previously associated with CR, such as growth hormone signalling, lipid metabolism and immune response. Moreover, our results highlight novel associations with CR, such as retinol metabolism and copper ion detoxification, as well as hint of a strong effect of CR on circadian rhythms that in turn may contribute to metabolic changes. Analyses of our signatures by integrating co-expression data, information on genetic mutants, and transcription factor binding site analysis revealed candidate regulators of transcriptional modules in CR. Our results hint at a transcriptional module involved in sterol metabolism regulated by Srebf1. A putative regulatory role of Ppara was also identified. Overall, our conserved molecular signatures of CR provide a comprehensive picture of CR-induced changes and help understand its regulatory mechanisms.

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

    Institute of Scientific and Technical Information of China (English)

    HUANG Xin; LI Hao-ming

    2009-01-01

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

  4. Exact p-value calculation for heterotypic clusters of regulatory motifs and its application in computational annotation of cis-regulatory modules

    Directory of Open Access Journals (Sweden)

    Roytberg Mikhail A

    2007-10-01

    Full Text Available Abstract Background cis-Regulatory modules (CRMs of eukaryotic genes often contain multiple binding sites for transcription factors. The phenomenon that binding sites form clusters in CRMs is exploited in many algorithms to locate CRMs in a genome. This gives rise to the problem of calculating the statistical significance of the event that multiple sites, recognized by different factors, would be found simultaneously in a text of a fixed length. The main difficulty comes from overlapping occurrences of motifs. So far, no tools have been developed allowing the computation of p-values for simultaneous occurrences of different motifs which can overlap. Results We developed and implemented an algorithm computing the p-value that s different motifs occur respectively k1, ..., ks or more times, possibly overlapping, in a random text. Motifs can be represented with a majority of popular motif models, but in all cases, without indels. Zero or first order Markov chains can be adopted as a model for the random text. The computational tool was tested on the set of cis-regulatory modules involved in D. melanogaster early development, for which there exists an annotation of binding sites for transcription factors. Our test allowed us to correctly identify transcription factors cooperatively/competitively binding to DNA. Method The algorithm that precisely computes the probability of simultaneous motif occurrences is inspired by the Aho-Corasick automaton and employs a prefix tree together with a transition function. The algorithm runs with the O(n|Σ|(m|ℋ MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacH8akY=wiFfYdH8Gipec8Eeeu0xXdbba9frFj0=OqFfea0dXdd9vqai=hGuQ8kuc9pgc9s8qqaq=dirpe0xb9q8qiLsFr0=vr0=vr0dc8meaabaqaciaacaGaaeqabaqabeGadaaakeaat0uy0HwzTfgDPnwy1egaryqtHrhAL1wy0L2yHvdaiqaacqWFlecsaaa@3762@| + K|σ|K ∏i ki time complexity, where n is the length of the text, |Σ| is the alphabet size, m is the

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

    Science.gov (United States)

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

    2016-12-23

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

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

    Science.gov (United States)

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

    2017-08-01

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

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

    Science.gov (United States)

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

    2014-03-01

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

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

    Science.gov (United States)

    2014-01-01

    Background Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. Methods We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. Results WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P < 0.001). Functional annotation identified pathways enlightening the association between obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and

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

    Science.gov (United States)

    Kogelman, Lisette J A; Cirera, Susanna; Zhernakova, Daria V; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

    2014-09-30

    Obesity is a complex metabolic condition in strong association with various diseases, like type 2 diabetes, resulting in major public health and economic implications. Obesity is the result of environmental and genetic factors and their interactions, including genome-wide genetic interactions. Identification of co-expressed and regulatory genes in RNA extracted from relevant tissues representing lean and obese individuals provides an entry point for the identification of genes and pathways of importance to the development of obesity. The pig, an omnivorous animal, is an excellent model for human obesity, offering the possibility to study in-depth organ-level transcriptomic regulations of obesity, unfeasible in humans. Our aim was to reveal adipose tissue co-expression networks, pathways and transcriptional regulations of obesity using RNA Sequencing based systems biology approaches in a porcine model. We selected 36 animals for RNA Sequencing from a previously created F2 pig population representing three extreme groups based on their predicted genetic risks for obesity. We applied Weighted Gene Co-expression Network Analysis (WGCNA) to detect clusters of highly co-expressed genes (modules). Additionally, regulator genes were detected using Lemon-Tree algorithms. WGCNA revealed five modules which were strongly correlated with at least one obesity-related phenotype (correlations ranging from -0.54 to 0.72, P obesity and other diseases, like osteoporosis (osteoclast differentiation, P = 1.4E-7), and immune-related complications (e.g. Natural killer cell mediated cytotoxity, P = 3.8E-5; B cell receptor signaling pathway, P = 7.2E-5). Lemon-Tree identified three potential regulator genes, using confident scores, for the WGCNA module which was associated with osteoclast differentiation: CCR1, MSR1 and SI1 (probability scores respectively 95.30, 62.28, and 34.58). Moreover, detection of differentially connected genes identified various genes previously identified to be

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

    NARCIS (Netherlands)

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

    2016-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiaodong Cai

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

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

    Science.gov (United States)

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

    1992-01-01

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

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

    Institute of Scientific and Technical Information of China (English)

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

    2009-01-01

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

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

    Science.gov (United States)

    He, Qinbin; Xia, Zhile; Lin, Bin

    2016-11-07

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

  16. 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.

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

    Science.gov (United States)

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

    2015-11-01

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

  18. 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.

  19. 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.

  20. Network discovery pipeline elucidates conserved time-of-day-specific cis-regulatory modules.

    Directory of Open Access Journals (Sweden)

    Todd P Michael

    2008-02-01

    Full Text Available Correct daily phasing of transcription confers an adaptive advantage to almost all organisms, including higher plants. In this study, we describe a hypothesis-driven network discovery pipeline that identifies biologically relevant patterns in genome-scale data. To demonstrate its utility, we analyzed a comprehensive matrix of time courses interrogating the nuclear transcriptome of Arabidopsis thaliana plants grown under different thermocycles, photocycles, and circadian conditions. We show that 89% of Arabidopsis transcripts cycle in at least one condition and that most genes have peak expression at a particular time of day, which shifts depending on the environment. Thermocycles alone can drive at least half of all transcripts critical for synchronizing internal processes such as cell cycle and protein synthesis. We identified at least three distinct transcription modules controlling phase-specific expression, including a new midnight specific module, PBX/TBX/SBX. We validated the network discovery pipeline, as well as the midnight specific module, by demonstrating that the PBX element was sufficient to drive diurnal and circadian condition-dependent expression. Moreover, we show that the three transcription modules are conserved across Arabidopsis, poplar, and rice. These results confirm the complex interplay between thermocycles, photocycles, and the circadian clock on the daily transcription program, and provide a comprehensive view of the conserved genomic targets for a transcriptional network key to successful adaptation.

  1. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    Wessler, S.

    1990-12-31

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

  3. Chromatin Modulation of Herpesvirus Lytic Gene Expression: Managing Nucleosome Density and Heterochromatic Histone Modifications

    Directory of Open Access Journals (Sweden)

    Thomas M. Kristie

    2016-03-01

    Full Text Available Like their cellular hosts, herpesviruses are subject to the regulatory impacts of chromatin assembled on their genomes. Upon infection, these viruses are assembled into domains of chromatin with heterochromatic signatures that suppress viral gene expression or euchromatic characteristics that promote gene expression. The organization and modulation of these chromatin domains appear to be intimately linked to the coordinated expression of the different classes of viral genes and thus ultimately play an important role in the progression of productive infection or the establishment and maintenance of viral latency. A recent report from the Knipe laboratory (J. S. Lee, P. Raja, and D. M. Knipe, mBio 7:e02007-15, 2016 contributes to the understanding of the dynamic modulation of chromatin assembled on the herpes simplex virus genome by monitoring the levels of characteristic heterochromatic histone modifications (histone H3 lysine 9 and 27 methylation associated with a model viral early gene during the progression of lytic infection. Additionally, this study builds upon previous observations that the viral immediate-early protein ICP0 plays a role in reducing the levels of heterochromatin associated with the early genes.

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

    Science.gov (United States)

    Nurse, P; Thuriaux, P

    1980-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Slavé Petrovski

    2015-09-01

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

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

    Science.gov (United States)

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

    2015-09-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  8. Structures and Boolean Dynamics in Gene Regulatory Networks

    Science.gov (United States)

    Szedlak, Anthony

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    OpenAIRE

    Nurse, Paul; Thuriaux, Pierre

    1980-01-01

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

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

    Science.gov (United States)

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

    2003-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Frank Emmert-Streib

    2013-02-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  14. Cloning and functional characterization of the 5' regulatory region of ovine Hormone Sensitive Lipase (HSL) gene.

    Science.gov (United States)

    Lampidonis, Antonis D; Stravopodis, Dimitrios J; Voutsinas, Gerassimos E; Messini-Nikolaki, Niki; Stefos, George C; Margaritis, Lukas H; Argyrokastritis, Alexandros; Bizelis, Iosif; Rogdakis, Emmanuel

    2008-12-31

    Hormone Sensitive Lipase (HSL) catalyzes the rate-limiting step in the mobilization of fatty acids from adipose tissue, thus determining the supply of energy substrates in the body. HSL enzymatic activity is increased by adrenergic agonists, such as catecholamines and glucagons, which induce cyclic AMP (cAMP) intracellular production, subsequently followed by the activation of Protein Kinase A (PKA) and its downstream signaling cascade reactions. HSL constitutes the critical enzyme in the modulation of lipid stores and the only component being subjected to hormonal control in terms of the recently identified Adipose Triglyceride Lipase (ATGL). In order to acquire detailed knowledge with regard to the mechanisms regulating ovine HSL (ovHSL) gene transcription activity, we initially isolated and cloned the 5' proximal and distal promoter regions through a genome walking approach, with the utilization of the already characterized ovHSL cDNAs. As evinced by BLAST analysis and a multiple alignment procedure, the isolated genomic fragment of 2.744 kb appeared to contain the already specified 5'-untranslated region (5'-UTR), which was interrupted by a relatively large intron of 1.448 kb. Regarding the upstream remaining part of 1.224 kb, it was demonstrated to represent a TATA-less promoter area, harboring several cis-regulatory elements that could be putatively recognized by relatively more general transcription factors, mainly including Stimulating protein 1 (Sp1), CCAAT-box Binding Factors (CBFs), Activator Protein 2 (AP2) and Glucocorticoid Receptor (GR), as well as other cis-acting regions denominated as Insulin Response Element (IRE), Glucose Response Element (GRE), Fat Specific Element (FSE) and cAMP Response Element (CRE), which could likely function in a nourishment (i.e. glucose)-/hormone-dependent fashion. When different genomic fragments were directionally (5' to 3') cloned into a suitable reporter vector upstream of a promoter-less luciferase gene and

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

    Science.gov (United States)

    Heath, Allison; Kavraki, Lydia; Balázsi, Gábor

    2008-03-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2014-04-24

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

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

    Directory of Open Access Journals (Sweden)

    Hironori Hojo

    2017-06-01

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

  19. 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

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

    Science.gov (United States)

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

    2016-07-01

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

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

    Science.gov (United States)

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

    2014-06-01

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

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

    NARCIS (Netherlands)

    Grzegorczyk, Marco; Husmeier, Dirk; Rahnenfuehrer, Joerg

    2011-01-01

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

  3. 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...

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  5. 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...

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

    NARCIS (Netherlands)

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

    2007-01-01

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

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

    Science.gov (United States)

    Sarkar, Poulomee; Sumby, Paul

    2017-02-01

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

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

    Directory of Open Access Journals (Sweden)

    Ehsan Sharif-Paghaleh

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

  9. SUMOylation modulates the transcriptional activity of androgen receptor in a target gene and pathway selective manner.

    Science.gov (United States)

    Sutinen, Päivi; Malinen, Marjo; Heikkinen, Sami; Palvimo, Jorma J

    2014-07-01

    Androgen receptor (AR) plays an important regulatory role in prostate cancer. AR's transcriptional activity is regulated by androgenic ligands, but also by post-translational modifications, such as SUMOylation. To study the role of AR SUMOylation in genuine chromatin environment, we compared androgen-regulated gene expression and AR chromatin occupancy in PC-3 prostate cancer cell lines stably expressing wild-type (wt) or doubly SUMOylation site-mutated AR (AR-K386R,K520R). Our genome-wide gene expression analyses reveal that the SUMOylation modulates the AR function in a target gene and pathway selective manner. The transcripts that are differentially regulated by androgen and SUMOylation are linked to cellular movement, cell death, cellular proliferation, cellular development and cell cycle. Fittingly, SUMOylation mutant AR cells proliferate faster and are more sensitive to apoptosis. Moreover, ChIP-seq analyses show that the SUMOylation can modulate the chromatin occupancy of AR on many loci in a fashion that parallels their differential androgen-regulated expression. De novo motif analyses reveal that FOXA1, C/EBP and AP-1 motifs are differentially enriched at the wtAR- and the AR-K386R,K520R-preferred genomic binding positions. Taken together, our data indicate that SUMOylation does not simply repress the AR activity, but it regulates AR's interaction with the chromatin and the receptor's target gene selection.

  10. GeNeDA: An Open-Source Workflow for Design Automation of Gene Regulatory Networks Inspired from Microelectronics.

    Science.gov (United States)

    Madec, Morgan; Pecheux, François; Gendrault, Yves; Rosati, Elise; Lallement, Christophe; Haiech, Jacques

    2016-10-01

    The topic of this article is the development of an open-source automated design framework for synthetic biology, specifically for the design of artificial gene regulatory networks based on a digital approach. In opposition to other tools, GeNeDA is an open-source online software based on existing tools used in microelectronics that have proven their efficiency over the last 30 years. The complete framework is composed of a computation core directly adapted from an Electronic Design Automation tool, input and output interfaces, a library of elementary parts that can be achieved with gene regulatory networks, and an interface with an electrical circuit simulator. Each of these modules is an extension of microelectronics tools and concepts: ODIN II, ABC, the Verilog language, SPICE simulator, and SystemC-AMS. GeNeDA is first validated on a benchmark of several combinatorial circuits. The results highlight the importance of the part library. Then, this framework is used for the design of a sequential circuit including a biological state machine.

  11. Natural variations in expression of regulatory and detoxification related genes under limiting phosphate and arsenate stress in Arabidopsis thaliana

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    Tapsi eShukla

    2015-10-01

    Full Text Available Abiotic stress including nutrient deficiency and heavy metal toxicity severely affects plant growth, development, and productivity. Genetic variations within and in between species are one of the important factors in establishing interactions and responses of plants with the environment. In the recent past, natural variations in Arabidopsis thaliana have been used to understand plant development and response towards different stresses at genetic level. Phosphorus (Pi deficiency negatively affects plant growth and metabolism and modulates expression of the genes involved in Pi homeostasis. Arsenate, As(V, a chemical analogue of Pi, is taken up by the plants via phosphate transport system. Studies suggest that during Pi deficiency, enhanced As(V uptake leads to increased toxicity in plants. Here, the natural variations in Arabidopsis have been utilized to study the As(V stress response under limiting Pi condition. The primary root length was compared to identify differential response of three Arabidopsis accessions (Col-0, Sij-1 and Slavi-1 under limiting Pi and As(V stress. To study the molecular mechanisms responsible for the differential response, comprehensive expression profiling of the genes involved in uptake, detoxification and regulatory mechanisms was carried out. Analysis suggests genetic variation-dependent regulatory mechanisms may affect differential response of Arabidopsis natural variants towards As(V stress under limiting Pi condition. Therefore, it is hypothesized that detailed analysis of the natural variations under multiple stress conditions might help in the better understanding of the biological processes involved in stress tolerance and adaptation.

  12. Computational design and designability of gene regulatory networks

    OpenAIRE

    Rodrigo Tarrega, Guillermo

    2012-01-01

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

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

    Science.gov (United States)

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

    2001-04-01

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

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

    Science.gov (United States)

    Uchida, Eriko; Igarashi, Yuka; Sato, Yoji

    2014-01-01

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

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

    NARCIS (Netherlands)

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

    2015-01-01

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

  16. Satellite DNA Modulates Gene Expression in the Beetle Tribolium castaneum after Heat Stress.

    Science.gov (United States)

    Feliciello, Isidoro; Akrap, Ivana; Ugarković, Đurđica

    2015-08-01

    Non-coding repetitive DNAs have been proposed to perform a gene regulatory role, however for tandemly repeated satellite DNA no such role was defined until now. Here we provide the first evidence for a role of satellite DNA in the modulation of gene expression under specific environmental conditions. The major satellite DNA TCAST1 in the beetle Tribolium castaneum is preferentially located within pericentromeric heterochromatin but is also dispersed as single repeats or short arrays in the vicinity of protein-coding genes within euchromatin. Our results show enhanced suppression of activity of TCAST1-associated genes and slower recovery of their activity after long-term heat stress relative to the same genes without associated TCAST1 satellite DNA elements. The level of gene suppression is not influenced by the distance of TCAST1 elements from the associated genes up to 40 kb from the genes' transcription start sites, but it does depend on the copy number of TCAST1 repeats within an element, being stronger for the higher number of copies. The enhanced gene suppression correlates with the enrichment of the repressive histone marks H3K9me2/3 at dispersed TCAST1 elements and their flanking regions as well as with increased expression of TCAST1 satellite DNA. The results reveal transient, RNAi based heterochromatin formation at dispersed TCAST1 repeats and their proximal regions as a mechanism responsible for enhanced silencing of TCAST1-associated genes. Differences in the pattern of distribution of TCAST1 elements contribute to gene expression diversity among T. castaneum strains after long-term heat stress and might have an impact on adaptation to different environmental conditions.

  17. Satellite DNA Modulates Gene Expression in the Beetle Tribolium castaneum after Heat Stress.

    Directory of Open Access Journals (Sweden)

    Isidoro Feliciello

    2015-08-01

    Full Text Available Non-coding repetitive DNAs have been proposed to perform a gene regulatory role, however for tandemly repeated satellite DNA no such role was defined until now. Here we provide the first evidence for a role of satellite DNA in the modulation of gene expression under specific environmental conditions. The major satellite DNA TCAST1 in the beetle Tribolium castaneum is preferentially located within pericentromeric heterochromatin but is also dispersed as single repeats or short arrays in the vicinity of protein-coding genes within euchromatin. Our results show enhanced suppression of activity of TCAST1-associated genes and slower recovery of their activity after long-term heat stress relative to the same genes without associated TCAST1 satellite DNA elements. The level of gene suppression is not influenced by the distance of TCAST1 elements from the associated genes up to 40 kb from the genes' transcription start sites, but it does depend on the copy number of TCAST1 repeats within an element, being stronger for the higher number of copies. The enhanced gene suppression correlates with the enrichment of the repressive histone marks H3K9me2/3 at dispersed TCAST1 elements and their flanking regions as well as with increased expression of TCAST1 satellite DNA. The results reveal transient, RNAi based heterochromatin formation at dispersed TCAST1 repeats and their proximal regions as a mechanism responsible for enhanced silencing of TCAST1-associated genes. Differences in the pattern of distribution of TCAST1 elements contribute to gene expression diversity among T. castaneum strains after long-term heat stress and might have an impact on adaptation to different environmental conditions.

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

    Directory of Open Access Journals (Sweden)

    Allan Andrew C

    2008-07-01

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

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

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    Tauch Andreas

    2009-01-01

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

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

    Science.gov (United States)

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

    2014-09-01

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

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

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    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.

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

    Science.gov (United States)

    2012-01-01

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

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

    DEFF Research Database (Denmark)

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

    2007-01-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Directory of Open Access Journals (Sweden)

    Lien Huang-Chun

    2009-03-01

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

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

    Science.gov (United States)

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

    2009-03-17

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

  7. Finding pathway-modulating genes from a novel Ontology Fingerprint-derived gene network.

    Science.gov (United States)

    Qin, Tingting; Matmati, Nabil; Tsoi, Lam C; Mohanty, Bidyut K; Gao, Nan; Tang, Jijun; Lawson, Andrew B; Hannun, Yusuf A; Zheng, W Jim

    2014-10-01

    To enhance our knowledge regarding biological pathway regulation, we took an integrated approach, using the biomedical literature, ontologies, network analyses and experimental investigation to infer novel genes that could modulate biological pathways. We first constructed a novel gene network via a pairwise comparison of all yeast genes' Ontology Fingerprints--a set of Gene Ontology terms overrepresented in the PubMed abstracts linked to a gene along with those terms' corresponding enrichment P-values. The network was further refined using a Bayesian hierarchical model to identify novel genes that could potentially influence the pathway activities. We applied this method to the sphingolipid pathway in yeast and found that many top-ranked genes indeed displayed altered sphingolipid pathway functions, initially measured by their sensitivity to myriocin, an inhibitor of de novo sphingolipid biosynthesis. Further experiments confirmed the modulation of the sphingolipid pathway by one of these genes, PFA4, encoding a palmitoyl transferase. Comparative analysis showed that few of these novel genes could be discovered by other existing methods. Our novel gene network provides a unique and comprehensive resource to study pathway modulations and systems biology in general. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

    Directory of Open Access Journals (Sweden)

    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.

  9. H-Ferritin-Regulated MicroRNAs Modulate Gene Expression in K562 Cells

    Science.gov (United States)

    Biamonte, Flavia; Zolea, Fabiana; Bisognin, Andrea; Di Sanzo, Maddalena; Saccoman, Claudia; Scumaci, Domenica; Aversa, Ilenia; Panebianco, Mariafranca; Faniello, Maria Concetta; Bortoluzzi, Stefania; Cuda, Giovanni; Costanzo, Francesco

    2015-01-01

    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. PMID:25815883

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

    Institute of Scientific and Technical Information of China (English)

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

    2011-01-01

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

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

    Science.gov (United States)

    Wang, Chen; Szaro, Ben G

    2016-01-01

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

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

    Science.gov (United States)

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

    2017-08-04

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

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

    Directory of Open Access Journals (Sweden)

    Kevin Y Yip

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

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

    Directory of Open Access Journals (Sweden)

    Angela Bruex

    2012-01-01

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

  15. Interferon Regulatory Factor 7 Promoted Glioblastoma Progression and Stemness by Modulating IL-6 Expression in Microglia

    Science.gov (United States)

    Li, Zongze; Huang, Qiming; Chen, Heping; Lin, Zhiqin; Zhao, Meng; Jiang, Zhongli

    2017-01-01

    Background: Interferon Regulatory Factor 7 (IRF7) is associated with chronic inflammation initiated by the activation of microglia. However it remains poorly defined how IRF7 activates microglia to initiate inflammatory microenvironment, and thus promotes the growth and malignancy of glioblastoma multiforme (GBM). This study investigated the role of IRF7 expression in microglia which increases GBM progression. Methods: We established stable human microglia (HMs) over-expressing IRF-7 or empty vector by lentiviral transduction and stable selection. These HM-IRF-7 cells were co-cultured with U87-MG to examine their influence on GBM, in terms of cell proliferation, apoptosis and stemness of U87-MG. By qRT-PCR and ELISA assays, the expression of key genes and secretion of inflammatory factors were identified in inflammatory signal pathway respectively. We also analyzed whether the expression of IRF7 and its target gene IL-6 correlated with PFS (progression-free survival) and OS (overall survival) in clinical samples by Kaplan-Meier survival curves. Results: HMs can be engineered to stably express high level of IFR7 with IRF7 lentivirus, and was found to promote U87-MG growth and inhibit its apoptosis in co-culture. Meanwhile, U87-MG seemed to show stem cell character with ALDH1 expression. These results may be related to IRF7 initiating IL-6 expression and secretion in both HM and U87-MG cells. The IRF7 and IL-6 were highly expressed in GBM tissues, and IL-6 secretion was high in GBM serums, both of which were significantly correlated with PFS and OS. Conclusions: The immune function of HMs was changed while it expressed IRF7 genes. The results demonstrated for the first time that IRF7 of microglia promoted GBM growth and stemness by mediating IL-6 expression, and revealed that IRF-7 and IL-6 were independent factors affecting the overall survival probability.

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

    Science.gov (United States)

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

    2016-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Gaurang Mahajan

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

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

    Science.gov (United States)

    Mahajan, Gaurang; Mande, Shekhar C

    2015-01-01

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

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

    Science.gov (United States)

    Tabbaa, Omar P.; Jayaprakash, C.

    2014-08-01

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

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

    Science.gov (United States)

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

    2004-12-15

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

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

    Science.gov (United States)

    Tabbaa, Omar P; Jayaprakash, C

    2014-08-01

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

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

    DEFF Research Database (Denmark)

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

    2006-01-01

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

  3. 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

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

    Directory of Open Access Journals (Sweden)

    Katz Jonathan D

    2004-10-01

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

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Rekin's Janky

    2014-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Rekin's Janky

    2014-07-01

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

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

    Science.gov (United States)

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

    2014-07-01

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

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

    Science.gov (United States)

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

    2017-01-01

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

  10. Co-expression module analysis reveals biological processes, genomic gain, and regulatory mechanisms associated with breast cancer progression

    Directory of Open Access Journals (Sweden)

    Derow Catherine K

    2010-05-01

    Full Text Available Abstract Background Gene expression signatures are typically identified by correlating gene expression patterns to a disease phenotype of interest. However, individual gene-based signatures usually suffer from low reproducibility and interpretability. Results We have developed a novel algorithm Iterative Clique Enumeration (ICE for identifying relatively independent maximal cliques as co-expression modules and a module-based approach to the analysis of gene expression data. Applying this approach on a public breast cancer dataset identified 19 modules whose expression levels were significantly correlated with tumor grade. The correlations were reproducible for 17 modules in an independent breast cancer dataset, and the reproducibility was considerably higher than that based on individual genes or modules identified by other algorithms. Sixteen out of the 17 modules showed significant enrichment in certain Gene Ontology (GO categories. Specifically, modules related to cell proliferation and immune response were up-regulated in high-grade tumors while those related to cell adhesion was down-regulated. Further analyses showed that transcription factors NYFB, E2F1/E2F3, NRF1, and ELK1 were responsible for the up-regulation of the cell proliferation modules. IRF family and ETS family proteins were responsible for the up-regulation of the immune response modules. Moreover, inhibition of the PPARA signaling pathway may also play an important role in tumor progression. The module without GO enrichment was found to be associated with a potential genomic gain in 8q21-23 in high-grade tumors. The 17-module signature of breast tumor progression clustered patients into subgroups with significantly different relapse-free survival times. Namely, patients with lower cell proliferation and higher cell adhesion levels had significantly lower risk of recurrence, both for all patients (p = 0.004 and for those with grade 2 tumors (p = 0.017. Conclusions The ICE

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

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    Iryna Kozmikova

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

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

    Science.gov (United States)

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

    2011-09-01

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

  13. Extracting expression modules from perturbational gene expression compendia

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    Van Dijck Patrick

    2008-04-01

    Full Text Available Abstract Background Compendia of gene expression profiles under chemical and genetic perturbations constitute an invaluable resource from a systems biology perspective. However, the perturbational nature of such data imposes specific challenges on the computational methods used to analyze them. In particular, traditional clustering algorithms have difficulties in handling one of the prominent features of perturbational compendia, namely partial coexpression relationships between genes. Biclustering methods on the other hand are specifically designed to capture such partial coexpression patterns, but they show a variety of other drawbacks. For instance, some biclustering methods are less suited to identify overlapping biclusters, while others generate highly redundant biclusters. Also, none of the existing biclustering tools takes advantage of the staple of perturbational expression data analysis: the identification of differentially expressed genes. Results We introduce a novel method, called ENIGMA, that addresses some of these issues. ENIGMA leverages differential expression analysis results to extract expression modules from perturbational gene expression data. The core parameters of the ENIGMA clustering procedure are automatically optimized to reduce the redundancy between modules. In contrast to the biclusters produced by most other methods, ENIGMA modules may show internal substructure, i.e. subsets of genes with distinct but significantly related expression patterns. The grouping of these (often functionally related patterns in one module greatly aids in the biological interpretation of the data. We show that ENIGMA outperforms other methods on artificial datasets, using a quality criterion that, unlike other criteria, can be used for algorithms that generate overlapping clusters and that can be modified to take redundancy between clusters into account. Finally, we apply ENIGMA to the Rosetta compendium of expression profiles for

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

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    Santillán Moisés

    2008-01-01

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

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

    Science.gov (United States)

    Chen, D B; Yang, H J

    2014-11-11

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

    Makai, Szabolcs; Tamás, László; Juhász, Angéla

    2016-01-01

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

  18. Transcription dynamics of inducible genes modulated by negative regulations.

    Science.gov (United States)

    Li, Yanyan; Tang, Moxun; Yu, Jianshe

    2015-06-01

    Gene transcription is a stochastic process in single cells, in which genes transit randomly between active and inactive states. Transcription of many inducible genes is also tightly regulated: It is often stimulated by extracellular signals, activated through signal transduction pathways and later repressed by negative regulations. In this work, we study the nonlinear dynamics of the mean transcription level of inducible genes modulated by the interplay of the intrinsic transcriptional randomness and the repression by negative regulations. In our model, we integrate negative regulations into gene activation process, and make the conventional assumption on the production and degradation of transcripts. We show that, whether or not the basal transcription is temporarily terminated when cells are stimulated, the mean transcription level grows in the typical up and down pattern commonly observed in immune response genes. With the help of numerical simulations, we clarify the delicate impact of the system parameters on the transcription dynamics, and demonstrate how our model generates the distinct temporal gene-induction patterns in mouse fibroblasts discerned in recent experiments.

  19. Localization of genes modulating the predisposition to schizophrenia: a revision

    Directory of Open Access Journals (Sweden)

    Lopes-Machado E.Z.

    2000-01-01

    Full Text Available The genetics of schizophrenia or bipolar affective disorder has advanced greatly at the molecular level since the introduction of probes for the localization of specific genes. Research on gene candidates for susceptibility to schizophrenia can broadly be divided into two types, i.e., linkage studies, where a gene is found near a specific DNA marker on a specific chromosome, and association studies, when a condition is associated with a specific allele of a specific gene. This review covers a decade of publications in this area, from the 1988 works of Bassett et al. and Sherrington et al. on a gene localized on the long arm of chromosome 5 at the 5q11-13 loci, to the 1997 work of Lin et al. pointing to the 13q14.1-q32 loci of chromosome 13 and to the 1998 work of Wright et al. on an HLA DRB1 gene locus on chromosome 6 at 6p21-3. The most replicated loci were those in the long arm of chromosome 22 (22q12-q13.1 and on the short arm of chromosome 6 (6p24-22. In this critical review of the molecular genetic studies involved in the localization of genes which modulate the predisposition to schizophrenia the high variability in the results obtained by different workers suggests that multiple loci are involved in the predisposition to this illness.

  20. 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

  1. Comparative RNA-Seq Analysis Reveals That Regulatory Network of Maize Root Development Controls the Expression of Genes in Response to N Stress.

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    Xiujing He

    Full Text Available Nitrogen (N is an essential nutrient for plants, and it directly affects grain yield and protein content in cereal crops. Plant root systems are not only critical for anchorage in the soil, but also for N acquisition. Therefore, genes controlling root development might also affect N uptake by plants. In this study, the responses of nitrogen on root architecture of mutant rtcs and wild-type of maize were investigated by morphological and physiological analysis. Subsequently, we performed a comparative RNA-Seq analysis to compare gene expression profiles between mutant rtcs roots and wild-type roots under different N conditions. We identified 786 co-modulated differentially expressed genes (DEGs related to root development. These genes participated in various metabolic processes. A co-expression cluster analysis and a cis-regulatory motifs analysis revealed the importance of the AP2-EREBP transcription factor family in the rtcs-dependent regulatory network. Some genotype-specific DEGs contained at least one LBD motif in their promoter region. Further analyses of the differences in gene transcript levels between rtcs and wild-type under different N conditions revealed 403 co-modulated DEGs with distinct functions. A comparative analysis revealed that the regulatory network controlling root development also controlled gene expression in response to N-deficiency. Several AP2-EREBP family members involved in multiple hormone signaling pathways were among the DEGs. These transcription factors might play important roles in the rtcs-dependent regulatory network related to root development and the N-deficiency response. Genes encoding the nitrate transporters NRT2-1, NAR2.1, NAR2.2, and NAR2.3 showed much higher transcript levels in rtcs than in wild-type under normal-N conditions. This result indicated that the LBD gene family mainly functions as transcriptional repressors, as noted in other studies. In summary, using a comparative RNA-Seq-based approach

  2. Comparative RNA-Seq Analysis Reveals That Regulatory Network of Maize Root Development Controls the Expression of Genes in Response to N Stress.

    Science.gov (United States)

    He, Xiujing; Ma, Haixia; Zhao, Xiongwei; Nie, Shujun; Li, Yuhua; Zhang, Zhiming; Shen, Yaou; Chen, Qi; Lu, Yanli; Lan, Hai; Zhou, Shufeng; Gao, Shibin; Pan, Guangtang; Lin, Haijian

    2016-01-01

    Nitrogen (N) is an essential nutrient for plants, and it directly affects grain yield and protein content in cereal crops. Plant root systems are not only critical for anchorage in the soil, but also for N acquisition. Therefore, genes controlling root development might also affect N uptake by plants. In this study, the responses of nitrogen on root architecture of mutant rtcs and wild-type of maize were investigated by morphological and physiological analysis. Subsequently, we performed a comparative RNA-Seq analysis to compare gene expression profiles between mutant rtcs roots and wild-type roots under different N conditions. We identified 786 co-modulated differentially expressed genes (DEGs) related to root development. These genes participated in various metabolic processes. A co-expression cluster analysis and a cis-regulatory motifs analysis revealed the importance of the AP2-EREBP transcription factor family in the rtcs-dependent regulatory network. Some genotype-specific DEGs contained at least one LBD motif in their promoter region. Further analyses of the differences in gene transcript levels between rtcs and wild-type under different N conditions revealed 403 co-modulated DEGs with distinct functions. A comparative analysis revealed that the regulatory network controlling root development also controlled gene expression in response to N-deficiency. Several AP2-EREBP family members involved in multiple hormone signaling pathways were among the DEGs. These transcription factors might play important roles in the rtcs-dependent regulatory network related to root development and the N-deficiency response. Genes encoding the nitrate transporters NRT2-1, NAR2.1, NAR2.2, and NAR2.3 showed much higher transcript levels in rtcs than in wild-type under normal-N conditions. This result indicated that the LBD gene family mainly functions as transcriptional repressors, as noted in other studies. In summary, using a comparative RNA-Seq-based approach, we identified

  3. Predictive screening for regulators of conserved functional gene modules (gene batteries in mammals

    Directory of Open Access Journals (Sweden)

    Sigvardsson Mikael

    2005-05-01

    Full Text Available Abstract Background The expression of gene batteries, genomic units of functionally linked genes which are activated by similar sets of cis- and trans-acting regulators, has been proposed as a major determinant of cell specialization in metazoans. We developed a predictive procedure to screen the mouse and human genomes and transcriptomes for cases of gene-battery-like regulation. Results In a screen that covered ~40 per cent of all annotated protein-coding genes, we identified 21 co-expressed gene clusters with statistically supported sharing of cis-regulatory sequence elements. 66 predicted cases of over-represented transcription factor binding motifs were validated against the literature and fell into three categories: (i previously described cases of gene battery-like regulation, (ii previously unreported cases of gene battery-like regulation with some support in a limited number of genes, and (iii predicted cases that currently lack experimental support. The novel predictions include for example Sox 17 and RFX transcription factor binding sites that were detected in ~10% of all testis specific genes, and HNF-1 and 4 binding sites that were detected in ~30% of all kidney specific genes respectively. The results are publicly available at http://www.wlab.gu.se/lindahl/genebatteries. Conclusion 21 co-expressed gene clusters were enriched for a total of 66 shared cis-regulatory sequence elements. A majority of these predictions represent novel cases of potential co-regulation of functionally coupled proteins. Critical technical parameters were evaluated, and the results and the methods provide a valuable resource for future experimental design.

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

    Science.gov (United States)

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

    2016-09-16

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

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

    Science.gov (United States)

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

    2017-01-31

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

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

    CERN Document Server

    Caselle, M; Provero, P

    2002-01-01

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

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

    Science.gov (United States)

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

    2013-07-19

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

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

    Directory of Open Access Journals (Sweden)

    Amina Noor

    2013-01-01

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

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

    Science.gov (United States)

    Kobayashi, Koichi; Hiraishi, Kunihiko

    2013-01-01

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

  10. 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.

  11. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-08-15

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

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

    Science.gov (United States)

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

    2016-03-01

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

  14. 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.

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

    DEFF Research Database (Denmark)

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

    2000-01-01

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

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

    OpenAIRE

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

    2016-01-01

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

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

    OpenAIRE

    1995-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

  19. The PSE1 gene modulates lead tolerance in Arabidopsis

    Science.gov (United States)

    Fan, Tingting; Yang, Libo; Wu, Xi; Ni, Jiaojiao; Jiang, Haikun; Zhang, Qi’an; Fang, Ling; Sheng, Yibao; Ren, Yongbing; Cao, Shuqing

    2016-01-01

    Lead (Pb) is a dangerous heavy metal contaminant with high toxicity to plants. However, the regulatory mechanism of plant Pb tolerance is poorly understood. Here, we showed that the PSE1 gene confers Pb tolerance in Arabidopsis. A novel Pb-sensitive mutant pse1-1 (Pb-sensitive1) was isolated by screening T-DNA insertion mutants. PSE1 encodes an unknown protein with an NC domain and was localized in the cytoplasm. PSE1 was induced by Pb stress, and the pse1-1 loss-of-function mutant showed enhanced Pb sensitivity; overexpression of PSE1 resulted in increased Pb tolerance. PSE1-overexpressing plants showed increased Pb accumulation, which was accompanied by the activation of phytochelatin (PC) synthesis and related gene expression. In contrast, the pse1-1 mutant showed reduced Pb accumulation, which was associated with decreased PC synthesis and related gene expression. In addition, the expression of PDR12 was also increased in PSE1-overexpressing plants subjected to Pb stress. Our results suggest that PSE1 regulates Pb tolerance mainly through glutathione-dependent PC synthesis by activating the expression of the genes involved in PC synthesis and at least partially through activating the expression of the ABC transporter PDR12/ABCG40. PMID:27335453

  20. 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.

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Science.gov (United States)

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

    2008-12-23

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

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

    Directory of Open Access Journals (Sweden)

    Jin'e Li

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

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

    Directory of Open Access Journals (Sweden)

    Xingguang Peng

    2016-10-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zijian Dong

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

  7. Repressive BMP2 gene regulatory elements near the BMP2 promoter

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-02-05

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

  8. 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

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

    Science.gov (United States)

    Thorne, Thomas

    2016-12-16

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

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

    Science.gov (United States)

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

    2017-02-15

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

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

    Directory of Open Access Journals (Sweden)

    Shungo Kano

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

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

    Science.gov (United States)

    Jia, Weizhang; Zhou, Xiuxia

    2010-05-15

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

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

    Science.gov (United States)

    Al Qazlan, Tuqyah Abdullah; Kara-Mohamed, Chafia

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Tuqyah Abdullah Al Qazlan

    2015-01-01

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

  15. Pax3 and Zic1 trigger the early neural crest gene regulatory network by the direct activation of multiple key neural crest specifiers.

    Science.gov (United States)

    Plouhinec, Jean-Louis; Roche, Daniel D; Pegoraro, Caterina; Figueiredo, Ana Leonor; Maczkowiak, Frédérique; Brunet, Lisa J; Milet, Cécile; Vert, Jean-Philippe; Pollet, Nicolas; Harland, Richard M; Monsoro-Burq, Anne H

    2014-02-15

    Neural crest development is orchestrated by a complex and still poorly understood gene regulatory network. Premigratory neural crest is induced at the lateral border of the neural plate by the combined action of signaling molecules and transcription factors such as AP2, Gbx2, Pax3 and Zic1. Among them, Pax3 and Zic1 are both necessary and sufficient to trigger a complete neural crest developmental program. However, their gene targets in the neural crest regulatory network remain unknown. Here, through a transcriptome analysis of frog microdissected neural border, we identified an extended gene signature for the premigratory neural crest, and we defined novel potential members of the regulatory network. This signature includes 34 novel genes, as well as 44 known genes expressed at the neural border. Using another microarray analysis which combined Pax3 and Zic1 gain-of-function and protein translation blockade, we uncovered 25 Pax3 and Zic1 direct targets within this signature. We demonstrated that the neural border specifiers Pax3 and Zic1 are direct upstream regulators of neural crest specifiers Snail1/2, Foxd3, Twist1, and Tfap2b. In addition, they may modulate the transcriptional output of multiple signaling pathways involved in neural crest development (Wnt, Retinoic Acid) through the induction of key pathway regulators (Axin2 and Cyp26c1). We also found that Pax3 could maintain its own expression through a positive autoregulatory feedback loop. These hierarchical inductions, feedback loops, and pathway modulations provide novel tools to understand the neural crest induction network.

  16. Precisely modulated pathogenicity island interference with late phage gene transcription.

    Science.gov (United States)

    Ram, Geeta; Chen, John; Ross, Hope F; Novick, Richard P

    2014-10-07

    Having gone to great evolutionary lengths to develop resistance to bacteriophages, bacteria have come up with resistance mechanisms directed at every aspect of the bacteriophage life cycle. Most genes involved in phage resistance are carried by plasmids and other mobile genetic elements, including bacteriophages and their relatives. A very special case of phage resistance is exhibited by the highly mobile phage satellites, staphylococcal pathogenicity islands (SaPIs), which carry and disseminate superantigen and other virulence genes. Unlike the usual phage-resistance mechanisms, the SaPI-encoded interference mechanisms are carefully crafted to ensure that a phage-infected, SaPI-containing cell will lyse, releasing the requisite crop of SaPI particles as well as a greatly diminished crop of phage particles. Previously described SaPI interference genes target phage functions that are not required for SaPI particle production and release. Here we describe a SaPI-mediated interference system that affects expression of late phage gene transcription and consequently is required for SaPI and phage. Although when cloned separately, a single SaPI gene totally blocks phage production, its activity in situ is modulated accurately by a second gene, achieving the required level of interference. The advantage for the host bacteria is that the SaPIs curb excessive phage growth while enhancing their gene transfer activity. This activity is in contrast to that of the clustered regularly interspaced short palindromic repeats (CRISPRs), which totally block phage growth at the cost of phage-mediated gene transfer. In staphylococci the SaPI strategy seems to have prevailed during evolution: The great majority of Staphylococcus aureus strains carry one or more SaPIs, whereas CRISPRs are extremely rare.

  17. Light Controlled Modulation of Gene Expression by Chemical Optoepigenetic Probes

    Science.gov (United States)

    Reis, Surya A.; Ghosh, Balaram; Hendricks, J. Adam; Szantai-Kis, D. Miklos; Törk, Lisa; Ross, Kenneth N.; Lamb, Justin; Read-Button, Willis; Zheng, Baixue; Wang, Hongtao; Salthouse, Christopher; Haggarty, Stephen J.; Mazitschek, Ralph

    2016-01-01

    Epigenetic gene regulation is a dynamic process orchestrated by chromatin-modifying enzymes. Many of these master regulators exert their function through covalent modification of DNA and histone proteins. Aberrant epigenetic processes have been implicated in the pathophysiology of multiple human diseases. Small-molecule inhibitors have been essential to advancing our understanding of the underlying molecular mechanisms of epigenetic processes. However, the resolution offered by small molecules is often insufficient to manipulate epigenetic processes with high spatio-temporal control. Here, we present a novel and generalizable approach, referred to as ‘Chemo-Optical Modulation of Epigenetically-regulated Transcription’ (COMET), enabling high-resolution, optical control of epigenetic mechanisms based on photochromic inhibitors of human histone deacetylases using visible light. COMET probes may translate into novel therapeutic strategies for diseases where conditional and selective epigenome modulation is required. PMID:26974814

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

    Science.gov (United States)

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

    2006-02-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Joeri Ruyssinck

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

  2. 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

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

    Science.gov (United States)

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

    2016-01-01

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

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

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    Weijia Zhang

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

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

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    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.

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

    Science.gov (United States)

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

    2012-09-15

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

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

    Science.gov (United States)

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

    2015-01-01

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

  8. Genomic analysis of host - Peste des petits ruminants vaccine viral transcriptome uncovers transcription factors modulating immune regulatory pathways.

    Science.gov (United States)

    Manjunath, Siddappa; Kumar, Gandham Ravi; Mishra, Bishnu Prasad; Mishra, Bina; Sahoo, Aditya Prasad; Joshi, Chaitanya G; Tiwari, Ashok K; Rajak, Kaushal Kishore; Janga, Sarath Chandra

    2015-02-24

    Peste des petits ruminants (PPR), is an acute transboundary viral disease of economic importance, affecting goats and sheep. Mass vaccination programs around the world resulted in the decline of PPR outbreaks. Sungri 96 is a live attenuated vaccine, widely used in Northern India against PPR. This vaccine virus, isolated from goat works efficiently both in sheep and goat. Global gene expression changes under PPR vaccine virus infection are not yet well defined. Therefore, in this study we investigated the host-vaccine virus interactions by infecting the peripheral blood mononuclear cells isolated from goat with PPRV (Sungri 96 vaccine virus), to quantify the global changes in the transcriptomic signature by RNA-sequencing. Viral genome of Sungri 96 vaccine virus was assembled from the PPRV infected transcriptome confirming the infection and demonstrating the feasibility of building a complete non-host genome from the blood transcriptome. Comparison of infected transcriptome with control transcriptome revealed 985 differentially expressed genes. Functional analysis showed enrichment of immune regulatory pathways under PPRV infection. Key genes involved in immune system regulation, spliceosomal and apoptotic pathways were identified to be dysregulated. Network analysis revealed that the protein - protein interaction network among differentially expressed genes is significantly disrupted in infected state. Several genes encoding TFs that govern immune regulatory pathways were identified to co-regulate the differentially expressed genes. These data provide insights into the host - PPRV vaccine virus interactome for the first time. Our findings suggested dysregulation of immune regulatory pathways and genes encoding Transcription Factors (TFs) that govern these pathways in response to viral infection.

  9. 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.

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

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    Hamid Vaez

    2014-01-01

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

  11. Gene expression profile of androgen modulated genes in the murine fetal developing lung

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    Côté Mélissa

    2010-01-01

    Full Text Available Abstract Background Accumulating evidences suggest that sex affects lung development. Indeed, a higher incidence of respiratory distress syndrome is observed in male compared to female preterm neonates at comparable developmental stage and experimental studies demonstrated an androgen-related delay in male lung maturation. However, the precise mechanisms underlying these deleterious effects of androgens in lung maturation are only partially understood. Methods To build up a better understanding of the effect of androgens on lung development, we analyzed by microarrays the expression of genes showing a sexual difference and those modulated by androgens. Lungs of murine fetuses resulting from a timely mating window of 1 hour were studied at gestational day 17 (GD17 and GD18, corresponding to the period of surge of surfactant production. Using injections of the antiandrogen flutamide to pregnant mice, we hunted for genes in fetal lungs which are transcriptionally modulated by androgens. Results Results revealed that 1844 genes were expressed with a sexual difference at GD17 and 833 at GD18. Many genes were significantly modulated by flutamide: 1597 at GD17 and 1775 at GD18. Datasets were analyzed by using in silico tools for reconstruction of cellular pathways. Between GD17 and GD18, male lungs showed an intensive transcriptional activity of proliferative pathways along with the onset of lung differentiation. Among the genes showing a sex difference or an antiandrogen modulation of their expression, we specifically identified androgen receptor interacting genes, surfactant related genes in particularly those involved in the pathway leading to phospholipid synthesis, and several genes of lung development regulator pathways. Among these latter, some genes related to Shh, FGF, TGF-beta, BMP, and Wnt signaling are modulated by sex and/or antiandrogen treatment. Conclusion Our results show clearly that there is a real delay in lung maturation between

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

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    Willadsen, Kai; Wiles, Janet

    2007-12-21

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

  13. 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.

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

    Science.gov (United States)

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

    2005-03-01

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

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

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    Lee Jae K

    2007-02-01

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

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

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

    2013-10-01

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

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

    Science.gov (United States)

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

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Xin Lai

    2013-01-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2008-12-23

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

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

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    Seo Hee W

    2010-09-01

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

  2. 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.

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

    Science.gov (United States)

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

    2017-01-03

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

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

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    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

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

    Science.gov (United States)

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

    2016-03-01

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

  6. A Network Partition Algorithm for Mining Gene Functional Modules of Colon Cancer from DNA Microarray Data

    Institute of Scientific and Technical Information of China (English)

    Xiao-Gang Ruan; Jin-Lian Wang; Jian-Geng Li

    2006-01-01

    Computational analysis is essential for transforming the masses of microarray data into a mechanistic understanding of cancer. Here we present a method for finding gene functional modules of cancer from microarray data and have applied it to colon cancer. First, a colon cancer gene network and a normal colon tissue gene network were constructed using correlations between the genes. Then the modules that tended to have a homogeneous functional composition were identified by splitting up the network. Analysis of both networks revealed that they are scale-free.Comparison of the gene functional modules for colon cancer and normal tissues showed that the modules' functions changed with their structures.

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

    Science.gov (United States)

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yue Fan

    2017-01-01

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

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

    DEFF Research Database (Denmark)

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

    2002-01-01

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

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

    Science.gov (United States)

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

    2016-06-15

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

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

    Science.gov (United States)

    Zhang, Kui; Busov, Victor; Wei, Hairong

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Yali Wang

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

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

    Science.gov (United States)

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

    2008-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Gelfand Mikhail S

    2005-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Streelman J Todd

    2011-05-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Catherine Guenther

    2008-12-01

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

  18. 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.

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

    OpenAIRE

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

    1988-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Min Kyung Sung

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Ana Maria Abreu Velez

    2015-01-01

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

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

    Science.gov (United States)

    Fish, Richard J; Neerman-Arbez, Marguerite

    2012-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Lukas Windhager

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

  4. REM sleep deprivation induces changes of down regulatory antagonist modulator (DREAM) expression in the ventrobasal thalamic nuclei of sprague-dawley rats.

    Science.gov (United States)

    Siran, Rosfaiizah; Ahmad, Asma Hayati; Abdul Aziz, Che Badariah; Ismail, Zalina

    2014-12-01

    REM sleep is a crucial component of sleep. Animal studies indicate that rapid eye movement (REM) sleep deprivation elicits changes in gene expression. Down regulatory antagonist modulator (DREAM) is a protein which downregulates other gene transcriptions by binding to the downstream response element site. The aim of this study is to examine the effect of REM sleep deprivation on DREAM expression in ventrobasal thalamic nuclei (VB) of rats. Seventy-two male Sprague-Dawley rats were divided into four major groups consisting of free-moving control rats (FMC) (n = 18), 72-h REM sleep-deprived rats (REMsd) (n = 18), 72-h REM sleep-deprived rats with 72-h sleep recovery (RG) (n = 18), and tank control rats (TC) (n = 18). REM sleep deprivation was elicited using the inverted flower pot technique. DREAM expression was examined in VB by immunohistochemical, Western blot, and quantitative real-time polymerase chain reaction (qRT-PCR) studies. The DREAM-positive neuronal cells (DPN) were decreased bilaterally in the VB of rats deprived of REM sleep as well as after sleep recovery. The nuclear DREAM extractions were increased bilaterally in animals deprived of REM sleep. The DREAM messenger RNA (mRNA) levels were decreased after sleep recovery. The results demonstrated a link between DREAM expression and REM sleep deprivation as well as sleep recovery which may indicate potential involvement of DREAM in REM sleep-induced changes in gene expression, specifically in nociceptive processing.

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

    Science.gov (United States)

    Moskon, Miha; Mraz, Miha

    2014-01-01

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

  6. MicroRNA Gene Regulatory Networks in Peripheral Nerve Sheath Tumors

    Science.gov (United States)

    2012-09-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2016-03-01

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

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

    Science.gov (United States)

    Paraboschi, Elvezia Maria; Cardamone, Giulia; Rimoldi, Valeria; Gemmati, Donato; Spreafico, Marta; Duga, Stefano; Soldà, Giulia; Asselta, Rosanna

    2015-09-30

    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.

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

    Science.gov (United States)

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

    2006-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Alexandra Saudemont

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

  12. Building gene expression signatures indicative of transcription factor activation to predict AOP modulation

    Science.gov (United States)

    Building gene expression signatures indicative of transcription factor activation to predict AOP modulation Adverse outcome pathways (AOPs) are a framework for predicting quantitative relationships between molecular initiatin...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2011-02-18

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

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

    Science.gov (United States)

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

    2010-07-20

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

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

    Science.gov (United States)

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

    2009-04-01

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

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

    Science.gov (United States)

    Chaouiya, Claudine; Ourrad, Ouerdia; Lima, Ricardo

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Claudine Chaouiya

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

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

    NARCIS (Netherlands)

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

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Anthony J E Berndt

    2015-12-01

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

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

    CERN Document Server

    Wollbold, Johannes; Ganter, Bernhard

    2008-01-01

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

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

    Science.gov (United States)

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

    2013-06-20

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

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

    Science.gov (United States)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

    Enhancers make up a huge class of genome regulatory elements that play an important role in the formation and maintenance of specific patterns of gene transcriptional activity in all types of cells. In recent years, high-throughput methods for the genome-wide epigenetic analysis of chromatin have made it possible to identify structural and functional features of enhancers and their role in the spatial and functional organization of the genome and in the formation and maintenance of cell identity, as well as in the pathogenesis of certain diseases. Special attention has been focused on genome regions called super-enhancers, or stretch enhancers, which consist of clusters of elements with properties of classic enhancers. This review considers current data on specific properties of super-enhancers and their role in the formation of interconnected autoregulatory circuits with positive feedback that regulates the most important genes, the activity of which underlies the formation and maintenance of specialized cellular functions.

  4. Robust and regulatory expression of defensin A gene driven by vitellogenin promoter in transgenic Anopheles stephensi

    Institute of Scientific and Technical Information of China (English)

    CHEN XiaoGuang; ZHANG YaJing; ZHENG XueLi; WANG ChunMei

    2007-01-01

    The use of genetically modified mosquitoes to reduce or replace field populations is a new strategy to control mosquito-borne diseases. The precondition of the implementation of this strategy is the ability to manipulate the genome of mosquitoes and to induce specific expression of the effector molecules driven by a suitable promoter. The objective of this study is to evaluate the expression of defensin A gene of Anopheles sinensis under the control of a vitellogenin promoter in transgenic Anopheles stephensi. The regulatory region of Anopheles gambiae vitellogenin was cloned and subcloned into transfer vector pSLFa consisting of an expression cassette with defensin A coding sequence. Then, the expression cassette was transferred into transformation vector pBac[3xP3-DsRedafm] using Asc I digestion. The recombinant plasmid DNA of pBac[3xP3DsRed-AgVgT2-DefA] and helper plasmid DNA of phsp-pBac were micro-injected into embryos of An. stephensi. The positive transgenic mosquitoes were screened by observing specific red fluorescence in the eyes of G1 larvae. Southern blot analysis showed that a single-copy transgene integrated into the genome of An. stephensi. RT-PCR analysis showed that the defensin A gene expressed specifically in fat bodies of female mosquitoes after a blood meal. Interestingly, the mRNA of defensin A is more stable compared with that of the endogenous vitellogenin gene. After multiple blood meals, the expression of defensin A appeared as a reducible and non-cycling type, a crucial feature for its anti-pathogen effect. From data above, we concluded that the regulatory function of the Vg promoter and the expression of defensin A gene were relatively conserved in different species of anopheles mosquitoes. These molecules could be used as candidates in the development of genetically modified mosquitoes.

  5. Putative cis-regulatory elements associated with heat shock genes activated during excystation of Cryptosporidium parvum.

    Directory of Open Access Journals (Sweden)

    Benjamin Cohn

    Full Text Available BACKGROUND: Cryptosporidiosis is a ubiquitous infectious disease, caused by the protozoan parasites Cryptosporidium hominis and C. parvum, leading to acute, persistent and chronic diarrhea worldwide. Although the complications of this disease can be serious, even fatal, in immunocompromised patients of any age, they have also been found to lead to long term effects, including growth inhibition and impaired cognitive development, in infected immunocompetent children. The Cryptosporidium life cycle alternates between a dormant stage, the oocyst, and a highly replicative phase that includes both asexual vegetative stages as well as sexual stages, implying fine genetic regulatory mechanisms. The parasite is extremely difficult to study because it cannot be cultured in vitro and animal models are equally challenging. The recent publication of the genome sequence of C. hominis and C. parvum has, however, significantly advanced our understanding of the biology and pathogenesis of this parasite. METHODOLOGY/PRINCIPAL FINDINGS: Herein, our goal was to identify cis-regulatory elements associated with heat shock response in Cryptosporidium using a combination of in silico and real time RT-PCR strategies. Analysis with Gibbs-Sampling algorithms of upstream non-translated regions of twelve genes annotated as heat shock proteins in the Cryptosporidium genome identified a highly conserved over-represented sequence motif in eleven of them. RT-PCR analyses, described herein and also by others, show that these eleven genes bearing the putative element are induced concurrent with excystation of parasite oocysts via heat shock. CONCLUSIONS/SIGNIFICANCE: Our analyses suggest that occurrences of a motif identified in the upstream regions of the Cryptosporidium heat shock genes represent parts of the transcriptional apparatus an