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Sample records for gene regulatory effects

  1. Contrasting Frequencies and Effects of cis- and trans-Regulatory Mutations Affecting Gene Expression

    PubMed Central

    Metzger, Brian P. H.; Duveau, Fabien; Yuan, David C.; Tryban, Stephen; Yang, Bing; Wittkopp, Patricia J.

    2016-01-01

    Heritable differences in gene expression are caused by mutations in DNA sequences encoding cis-regulatory elements and trans-regulatory factors. These two classes of regulatory change differ in their relative contributions to expression differences in natural populations because of the combined effects of mutation and natural selection. Here, we investigate how new mutations create the regulatory variation upon which natural selection acts by quantifying the frequencies and effects of hundreds of new cis- and trans-acting mutations altering activity of the TDH3 promoter in the yeast Saccharomyces cerevisiae in the absence of natural selection. We find that cis-regulatory mutations have larger effects on expression than trans-regulatory mutations and that while trans-regulatory mutations are more common overall, cis- and trans-regulatory changes in expression are equally abundant when only the largest changes in expression are considered. In addition, we find that cis-regulatory mutations are skewed toward decreased expression while trans-regulatory mutations are skewed toward increased expression. We also measure the effects of cis- and trans-regulatory mutations on the variability in gene expression among genetically identical cells, a property of gene expression known as expression noise, finding that trans-regulatory mutations are much more likely to decrease expression noise than cis-regulatory mutations. Because new mutations are the raw material upon which natural selection acts, these differences in the frequencies and effects of cis- and trans-regulatory mutations should be considered in models of regulatory evolution. PMID:26782996

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

    PubMed Central

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

    2015-01-01

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

  3. Topological effects of data incompleteness of gene regulatory networks

    PubMed Central

    2012-01-01

    Background The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly. Results In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different levels. Conclusions In doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis. PMID:22920968

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

    PubMed Central

    Kobayashi, Koichi; Hiraishi, Kunihiko

    2013-01-01

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

  5. Optimal control of gene regulatory networks with effectiveness of multiple drugs: a Boolean network approach.

    PubMed

    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.

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

    PubMed Central

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

    1990-01-01

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

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

    PubMed Central

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

    2015-01-01

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

  8. Effect of Regulatory Element DNA Methylation on Tissue-Type Plasminogen Activator Gene Expression

    PubMed Central

    Rivier-Cordey, Anne-Sophie; Caetano, Carlos; Fish, Richard J.; Kruithof, Egbert K. O.

    2016-01-01

    Expression of the tissue-type plasminogen activator gene (t-PA; gene name PLAT) is regulated, in part, by epigenetic mechanisms. We investigated the relationship between PLAT methylation and PLAT expression in five primary human cell types and six transformed cell lines. CpG methylation was analyzed in the proximal PLAT gene promoter and near the multihormone responsive enhancer (MHRE) -7.3 kilobase pairs upstream of the PLAT transcriptional start site (TSS, -7.3 kb). In Bowes melanoma cells, the PLAT promoter and the MHRE were fully unmethylated and t-PA secretion was extremely high. In other cell types the region from -647 to -366 was fully methylated, whereas an unmethylated stretch of DNA from -121 to +94 was required but not sufficient for detectable t-PA mRNA and t-PA secretion. DNA methylation near the MHRE was not correlated with t-PA secretion. Specific methylation of the PLAT promoter region -151 to +151, inserted into a firefly luciferase reporter gene, abolished reporter gene activity. The region -121 to + 94 contains two well-described regulatory elements, a PMA-responsive element (CRE) near -106 and a GC-rich region containing an Sp1 binding site near +59. Methylation of double-stranded DNA oligonucleotides containing the CRE or the GC-rich region had little or no effect on transcription factor binding. Methylated CpGs may attract co-repressor complexes that contain histone deacetylases (HDAC). However, reporter gene activity of methylated plasmids was not restored by the HDAC inhibitor trichostatin. In conclusion, efficient PLAT gene expression requires a short stretch of unmethylated CpG sites in the proximal promoter. PMID:27973546

  9. Polymorphism in regulatory gene sequences

    PubMed Central

    Mitchison, N A

    2001-01-01

    The extensive polymorphism revealed in non-coding gene-regulatory sequences, particularly in the immune system, suggests that this type of genetic variation is functionally and evolutionarily far more important than has been suspected, and provides a lead to new therapeutic strategies. PMID:11178274

  10. Modeling gene regulatory network motifs using statecharts

    PubMed Central

    2012-01-01

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

  11. Plant Evolution: Evolving Antagonistic Gene Regulatory Networks.

    PubMed

    Cooper, Endymion D

    2016-06-20

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

  12. Gene regulatory effects of disease-associated variation in the NRF2 network.

    PubMed

    Lacher, Sarah E; Slattery, Matthew

    2016-12-01

    Reactive oxygen species (ROS), which are both a natural byproduct of oxidative metabolism and an undesirable byproduct of many environmental stressors, can damage all classes of cellular macromolecules and promote diseases from cancer to neurodegeneration. The actions of ROS are mitigated by the transcription factor NRF2, which regulates expression of antioxidant genes via its interaction with cis-regulatory antioxidant response elements (AREs). However, despite the seemingly straightforward relationship between the opposing forces of ROS and NRF2, regulatory precision in the NRF2 network is essential. Genetic variants that alter NRF2 stability or alter ARE sequences have been linked to a range of diseases. NRF2 hyperactivating mutations are associated with tumorigenesis. On the subtler end of the spectrum, single nucleotide variants (SNVs) that alter individual ARE sequences have been linked to neurodegenerative disorders including progressive supranuclear palsy and Parkinson's disease, as well as other diseases. Although the human health implications of NRF2 dysregulation have been recognized for some time, a systems level view of this regulatory network is beginning to highlight key NRF2-targeted AREs consistently associated with disease.

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

    Singhal, Amit; Kumar, Pavanish; de Libero, Gennaro; Poidinger, Michael; Monterola, Christopher

    2015-01-01

    Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript. PMID:26393364

  15. Expression and Regulatory Effects of Murine Schlafen (Slfn) Genes in Malignant Melanoma and Renal Cell Carcinoma*

    PubMed Central

    Mavrommatis, Evangelos; Arslan, Ahmet Dirim; Sassano, Antonella; Hua, Youjia; Kroczynska, Barbara; Platanias, Leonidas C.

    2013-01-01

    There is emerging evidence that the IFN-inducible family of Slfn genes and proteins play important roles in cell cycle progression and control of cellular proliferation, but the precise functional roles of different Slfn members in the regulation of tumorigenesis remain unclear. In the present study, we undertook a systematic analysis on the expression and functional relevance of different mouse Slfn genes in malignant melanoma and renal cell carcinoma cells. Our studies demonstrate that several mouse Slfn genes are up-regulated in response to IFN treatment of mouse melanoma and renal cell carcinoma cells, including Slfn1, Slfn2, Slfn4, Slfn5, and Slfn8. Our data show that Slfn2 and Slfn3 play essential roles in the control of mouse malignant melanoma cell proliferation and/or anchorage-independent growth, suggesting key and non-overlapping roles for these genes in the control of malignant melanoma tumorigenesis. In renal cell carcinoma cells, in addition to Slfn2 and Slfn3, Slfn5 also exhibits important antineoplastic effects. Altogether, our findings indicate important functions for distinct mouse Slfn genes in the control of tumorigenesis and provide evidence for differential involvement of distinct members of this gene family in controlling tumorigenesis. They also raise the potential of future therapeutic approaches involving modulation of expression of members of this family of genes in malignant melanoma and renal cell carcinoma. PMID:24089532

  16. Expression and regulatory effects of murine Schlafen (Slfn) genes in malignant melanoma and renal cell carcinoma.

    PubMed

    Mavrommatis, Evangelos; Arslan, Ahmet Dirim; Sassano, Antonella; Hua, Youjia; Kroczynska, Barbara; Platanias, Leonidas C

    2013-11-15

    There is emerging evidence that the IFN-inducible family of Slfn genes and proteins play important roles in cell cycle progression and control of cellular proliferation, but the precise functional roles of different Slfn members in the regulation of tumorigenesis remain unclear. In the present study, we undertook a systematic analysis on the expression and functional relevance of different mouse Slfn genes in malignant melanoma and renal cell carcinoma cells. Our studies demonstrate that several mouse Slfn genes are up-regulated in response to IFN treatment of mouse melanoma and renal cell carcinoma cells, including Slfn1, Slfn2, Slfn4, Slfn5, and Slfn8. Our data show that Slfn2 and Slfn3 play essential roles in the control of mouse malignant melanoma cell proliferation and/or anchorage-independent growth, suggesting key and non-overlapping roles for these genes in the control of malignant melanoma tumorigenesis. In renal cell carcinoma cells, in addition to Slfn2 and Slfn3, Slfn5 also exhibits important antineoplastic effects. Altogether, our findings indicate important functions for distinct mouse Slfn genes in the control of tumorigenesis and provide evidence for differential involvement of distinct members of this gene family in controlling tumorigenesis. They also raise the potential of future therapeutic approaches involving modulation of expression of members of this family of genes in malignant melanoma and renal cell carcinoma.

  17. On attractors in gene regulatory systems

    NASA Astrophysics Data System (ADS)

    Brokan, E.; Sadyrbaev, F. Zh.

    2017-02-01

    We describe attracting sets for differential systems appearing in mathematical models of gene regulatory systems. The relation of elements in such systems can be described by regulatory matrices containing elements -1, 0 or 1 corresponding to inhibition, no relation or activation respectively. Four types of regulatory matrices are considered. The respective examples are discussed and the attractive sets are described.

  18. The Effects of Sequence Variation on Genome-wide NRF2 Binding—New Target Genes and Regulatory SNPs

    PubMed Central

    Kuosmanen, Suvi M.; Viitala, Sari; Laitinen, Tuomo; Peräkylä, Mikael; Pölönen, Petri; Kansanen, Emilia; Leinonen, Hanna; Raju, Suresh; Wienecke-Baldacchino, Anke; Närvänen, Ale; Poso, Antti; Heinäniemi, Merja; Heikkinen, Sami; Levonen, Anna-Liisa

    2016-01-01

    Transcription factor binding specificity is crucial for proper target gene regulation. Motif discovery algorithms identify the main features of the binding patterns, but the accuracy on the lower affinity sites is often poor. Nuclear factor E2-related factor 2 (NRF2) is a ubiquitous redox-activated transcription factor having a key protective role against endogenous and exogenous oxidant and electrophile stress. Herein, we decipher the effects of sequence variation on the DNA binding sequence of NRF2, in order to identify both genome-wide binding sites for NRF2 and disease-associated regulatory SNPs (rSNPs) with drastic effects on NRF2 binding. Interactions between NRF2 and DNA were studied using molecular modelling, and NRF2 chromatin immunoprecipitation-sequence datasets together with protein binding microarray measurements were utilized to study binding sequence variation in detail. The binding model thus generated was used to identify genome-wide binding sites for NRF2, and genomic binding sites with rSNPs that have strong effects on NRF2 binding and reside on active regulatory elements in human cells. As a proof of concept, miR-126–3p and -5p were identified as NRF2 target microRNAs, and a rSNP (rs113067944) residing on NRF2 target gene (Ferritin, light polypeptide, FTL) promoter was experimentally verified to decrease NRF2 binding and result in decreased transcriptional activity. PMID:26826707

  19. Regulatory genes in the ancestral chordate genomes.

    PubMed

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

    2008-12-01

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

  20. Cell cycle regulatory effects of retinoic Acid and forskolin are mediated by the cyclin C gene.

    PubMed

    Makkonen, Katri M; Malinen, Marjo; Ropponen, Antti; Väisänen, Sami; Carlberg, Carsten

    2009-10-23

    As a partner of cyclin-dependent kinase (CDK) 3, Cyclin C controls cellular proliferation and, together with CDK8, represses gene transcription. In this study, we showed that the highly expressed Cyclin C gene is a direct target of the nuclear hormone all-trans retinoic acid (RA) in HEK293 human embryonal kidney cells. The RA receptor (RAR) gamma associates with a Cyclin C promoter region containing two RAR binding sites. The Cyclin C gene also directly responds to the cAMP activator Forskolin via the transcription factor CREB1 (cAMP response element-binding protein 1), for which we identified four binding sites within the first 2250 bp of its promoter. RARgamma and CREB1 show functional convergence via the corepressor NCoR1, which controls in particular the Forskolin response of Cyclin C. The histone deacetylases 1, 5, 6, 7 and 11 are involved in the basal expression of Cyclin C, but in HEK293 and MCF-7 human breast carcinoma cells the antiproliferative effects of the histone deacetylase inhibitor SAHA (suberoylanilide hydroxamic acid) are not mediated by Cyclin C. However, cell cycle progressing effects of all-trans RA and Forskolin are dependent on Cyclin C expression levels. This suggests that the primary regulation of Cyclin C by all-trans RA and Forskolin mediates some of the cell cycle control actions of these compounds.

  1. Evolving Robust Gene Regulatory Networks

    PubMed Central

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

    2015-01-01

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

  2. Modeling of hysteresis in gene regulatory networks.

    PubMed

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

    2012-08-01

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

  3. Regulatory effects of genomic translocations at the human carboxylesterase-1 (CES1) gene locus.

    PubMed

    Sanford, Jonathan C; Wang, Xinwen; Shi, Jian; Barrie, Elizabeth S; Wang, Danxin; Zhu, Hao-Jie; Sadee, Wolfgang

    2016-05-01

    CES1 encodes carboxylesterase-1, an important drug-metabolizing enzyme with high expression in the liver. Previous studies have reported a genomic translocation of the 5' region from the poorly expressed pseudogene CES1P1, to CES1, yielding the structural variant CES1VAR. The aim of this study was to characterize this translocation and its effect on CES1 expression in the human liver. Experiments were conducted in human liver tissues and cell culture (HepG2). The promoter and exon 1 of CES1 were sequenced by Sanger and Ion Torrent sequencing to identify gene translocations. The effects of CES1 5'UTRs on mRNA and protein expression were assessed by quantitative real-time PCR, allelic ratio mRNA analysis by primer extension (SNaPshot), quantitative targeted proteomics, and luciferase reporter gene assays. Sequencing of CES1 identified two translocations: first, CES1VAR (17% minor allele frequency) comprising the 5'UTR, exon 1, and part of intron 1. A second shorter translocation, CES1SVAR, was observed excluding exon 1 and intron 1 regions (<0.01% minor allele frequency). CES1VAR is associated with 2.6-fold decreased CES1 mRNA and ∼1.35-fold lower allelic mRNA. Luciferase reporter constructs showed that CES1VAR decreases luciferase activity 1.5-fold, whereas CES1SVAR slightly increases activity. CES1VAR was not associated with CES1 protein expression or metabolism of the CES1 substrates enalapril, clopidogrel, or methylphenidate in the liver. The frequent translocation variant CES1VAR reduces mRNA expression of CES1 in the liver by ∼30%, but protein expression and metabolizing activity in the liver were not detectably altered - possibly because of variable CES1 expression masking small allelic effects. Whether drug therapies are affected by CES1VAR will require further in-vivo studies.

  4. [Effect of pingxian granules on protein expression of apoptosis regulatory genes in hippocampus of pentylenetetrazol-induced epileptic model rats].

    PubMed

    Tian, Rong; She, Yali; Jia, Yuxin; Wang, Yu; Cheng, Xiaoli; Mu, Baolong

    2012-05-01

    To observe the effect of Pingxian granules on the protein expression of apoptosis regulatory genes Bcl-2 and Bax in the hippocampus of epileptic model rats and study the molecular biological mechanism of the anti-epileptic effect of Pingxian granules. Totally 60 45-days-old Wistar rats were selected and then randomly assigned into 5 groups: the normal control group, the model group, the positive control group, the Pingxian high dose group and the Pingxian low dose group, with 12 in each group. Except the normal control group, all the groups were intraperitoneally injected with 35 mg x kg(-1) pentylenetetrazol to establish the models of epilepsy. The Pingxian high dose (1.66 g x mL(-1)) and low dose (0.42 g x mL(-1)) groups were intragastrically infused with Pingxian granules 2 mL x d(-1). The positive control group received 3.6 g x L(-1) phenobarbital suspension by gastric perfusion. The normal group and the model group were drenched with distilled water, 2 mL x d(-1), for 5 weeks. Bcl-2 and Bax protein positive cells were labeled with immunohistochemical SABC at 3, 5 w. (1) Rats in the model group appeared the epileptic behavior at the 1st week, and became serious with the kindle frequency; grade VIepileptic behavior appeared at the 4th week. The attack frequency and grade of the Pingxian group were less and lower, the highest grade were only IV, and there were no significant differences in the attack grade and frequency. (2) With the increase in kindle frequency, the model group showed a notable decrease in the Bcl-2 expression compared with the normal control group at the 3rd and 5th weekend (P < 0.01), but a significant increase in Bax protein expression (P <0. 01). The number of the Bcl-2 protein expression in Pingxian groups and the positive control group were obviously more than the model group (P < 0.01); and the number of the Bax protein expression in Pingxian groups and the positive control group were obviously less than the model group (P < 0

  5. ASSEMBLING NEURAL CREST REGULATORY CIRCUITS INTO A GENE REGULATORY NETWORK

    PubMed Central

    Betancur, Paola; Bronner-Fraser, Marianne; Sauka-Spengler, Tatjana

    2014-01-01

    The neural crest is a multipotent stem cell--like population that gives rise to a wide range of derivatives in vertebrate embryo including elements of the craniofacial skeleton and peripheral nervous system as well as melanocytes. The neural crest forms in a series of regulatory steps that include induction and specification of the prospective neural crest territory--neural plate border, specification of bona fide neural crest progenitors, and differentiation into diverse derivatives. These individual processes during neural crest ontogeny are controlled by regulatory circuits that can be assembled into a hierarchical gene regulatory network (GRN). Here we present an overview of the GRN that orchestrates the formation of cranial neural crest cells. Formulation of this network relies on information largely inferred from gene perturbation studies performed in several vertebrate model organisms. Our representation of the cranial neural crest GRN also includes information about direct regulatory interactions obtained from the cis-regulatory analyses performed to date, which increases the resolution of the architectural circuitry within the network. PMID:19575671

  6. Plant nitrogen regulatory P-PII genes

    DOEpatents

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

    2001-01-01

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

  7. Regulatory effects of introduction of an exogenous FGF2 gene on other growth factor genes in a healing tendon.

    PubMed

    Tang, Jin Bo; Chen, Chuan Hao; Zhou, You Lang; McKeever, Clarie; Liu, Paul Y

    2014-01-01

    In this study of a tendon injury model, we investigated how injection of a vector incorporating one growth factor gene changes expression levels of multiple growth factor genes in the healing process. The flexor tendon of chicken toes was completely cut and repaired surgically. The tendons in the experimental arm were injected with an adeno-associated virus-2 vector incorporating basic fibroblast growth-factor gene, whereas the tendons in the control arm were not injected or injected with sham vectors. Using real-time polymerase chain reaction, we found that, within the tendon healing period, a set of growth factor genes-transforming growth factor-β1, vascular endothelial growth factor, and connective tissue growth factor-were significantly up-regulated. Expression of the platelet-derived growth factor-B gene was not changed, and the insulin-like growth factor was down-regulated. A tendon marker gene, scleraxis, was significantly up-regulated in the period. Our study revealed an intriguing finding that introduction of one growth factor gene in the healing tendon modulated expression of multiple growth factor genes. We believe this study may have significant implications in determining the approach of gene therapy, and the findings substantiate that gene therapy using a single growth factor could affect multiple growth factors.

  8. Effect of antibiotic down-regulatory gene wblA ortholog on antifungal polyene production in rare actinomycetes Pseudonocardia autotrophica.

    PubMed

    Kim, Hye-Jin; Kim, Min-Kyung; Jin, Ying-Yu; Kim, Young-Woo; Kim, Eung-Soo

    2014-09-01

    The rare actinomycete Pseudonocardia autotrophica was previously shown to produce a solubilityimproved toxicity-reduced novel polyene compound named Nystatin-like Pseudonocardia Polyene (NPP). The low productivity of NPP in P. autotrophica implies that its biosynthetic pathway is tightly regulated. In this study, wblApau was isolated and identified as a novel negative regulatory gene for NPP production in P. autotrophica, which showed approximately 49% amino acid identity with a global antibiotic down-regulatory gene, wblA, identified from various Streptomycetes species. Although no significant difference in NPP production was observed between P. autotrophica harboring empty vector and the S. coelicolor wblA under its native promoter, approximately 12% less NPP was produced in P. autotrophica expressing the wblA gene under the strong constitutive ermE(*) promoter. Furthermore, disruption of the wblApau gene from P. autotrophica resulted in an approximately 80% increase in NPP productivity. These results strongly suggest that identification and inactivation of the global antibiotic down-regulatory gene wblA ortholog are a critical strategy for improving secondary metabolite overproduction in not only Streptomyces but also non-Streptomyces rare actinomycete species.

  9. Misregulation of spermatogenesis genes in Drosophila hybrids is lineage-specific and driven by the combined effects of sterility and fast male regulatory divergence.

    PubMed

    Gomes, S; Civetta, A

    2014-09-01

    Hybrid male sterility is a common outcome of crosses between different species. Gene expression studies have found that a number of spermatogenesis genes are differentially expressed in sterile hybrid males, compared with parental species. Late-stage sperm development genes are particularly likely to be misexpressed, with fewer early-stage genes affected. Thus, a link has been posited between misexpression and sterility. A more recent alternative explanation for hybrid gene misexpression has been that it is independent of sterility and driven by divergent evolution of male-specific regulatory elements between species (faster male hypothesis). The faster male hypothesis predicts that misregulation of spermatogenesis genes should be independent of sterility and approximately the same in both hybrids, whereas sterility should only affect gene expression in sterile hybrids. To test the faster male hypothesis vs. the effect of sterility on gene misexpression, we analyse spermatogenesis gene expression in different species pairs of the Drosophila phylogeny, where hybrid male sterility occurs in only one direction of the interspecies cross (i.e. unidirectional sterility). We find significant differences among genes in misexpression with effects that are lineage-specific and caused by sterility or fast male regulatory divergence. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

  10. [Inductive effect of zinc oxide nanoparticles on interleukin 8 gene expression in human bronchial epithelial cells and its regulatory mechanism].

    PubMed

    Lu, Yang; Xu, Lei; Yan, Zhen; Wu, Yi-ming; Wu, Wei-dong

    2013-02-01

    To clarify the effect of zinc oxide nanoparticles (ZnO-NPs) (30 nm in diameter) on the interleukin 8 (IL-8) gene expression in human bronchial epithelial cells (BEAS-2B) and its regulatory mechanism. BEAS-2B cells were used in the study. The MTT assay was employed to evaluate the damage to BEAS-2B cells by ZnO-NPs. RT-PCR and ELISA were used to measure the mRNA and protein expression levels of IL-8 in the BEAS-2B cells exposed to ZnO-NPs. The IL-8 mRNA decay assay was used to determine the effect of ZnO-NPs on IL-8 mRNA stability. Exposure to ZnO-NPs significantly increased the level of IL-8 mRNA in BEAS-2B cells and the level of IL-8 protein in supernatant medium. The transcription inhibitor significantly reduced the mRNA expression of IL-8 induced by ZnO-NPs. ZnO-NPs significantly delayed IL-8 mRNA degradation in the BEAS-2B cells that were pretreated with actinomycin D for terminating IL-8 mRNA synthesis. ZnO-NPs can increase the mRNA and protein expression levels of IL-8 and IL-8 mRNA stability in BEAS-2B cells.

  11. Regulatory mechanisms for floral homeotic gene expression.

    PubMed

    Liu, Zhongchi; Mara, Chloe

    2010-02-01

    Proper regulation of floral homeotic gene (or ABCE gene) expression ensures the development of floral organs in the correct number, type, and precise spatial arrangement. This review summarizes recent advances on the regulation of floral homeotic genes, highlighting the variety and the complexity of the regulatory mechanisms involved. As flower development is one of the most well characterized developmental processes in higher plants, it facilitates the discovery of novel regulatory mechanisms. To date, mechanisms for the regulation of floral homeotic genes range from transcription to post-transcription, from activators to repressors, and from microRNA- to ubiquitin-mediated post-transcriptional regulation. Region-specific activation of floral homeotic genes is dependent on the integration of a flower-specific activity provided by LEAFY (LFY) and a region- and stage-specific activating function provided by one of the LFY cofactors. Two types of regulatory loops, the feed-forward and the feedback loop, provide properly timed gene activation and subsequent maintenance and refinement in proper spatial and temporal domains of ABCE genes. Two different microRNA/target modules may have been independently recruited in different plant species to regulate C gene expression. Additionally, competition among different MADS box proteins for common interacting partners may represent a mechanism in whorl boundary demarcation. Future work using systems approaches and the development of non-model plants will provide integrated views on floral homeotic gene regulation and insights into the evolution of morphological diversity in flowering plants. Copyright 2009 Elsevier Ltd. All rights reserved.

  12. Cis-by-Trans Regulatory Divergence Causes the Asymmetric Lethal Effects of an Ancestral Hybrid Incompatibility Gene

    PubMed Central

    Maheshwari, Shamoni; Barbash, Daniel A.

    2012-01-01

    The Dobzhansky and Muller (D-M) model explains the evolution of hybrid incompatibility (HI) through the interaction between lineage-specific derived alleles at two or more loci. In agreement with the expectation that HI results from functional divergence, many protein-coding genes that contribute to incompatibilities between species show signatures of adaptive evolution, including Lhr, which encodes a heterochromatin protein whose amino acid sequence has diverged extensively between Drosophila melanogaster and D. simulans by natural selection. The lethality of D. melanogaster/D. simulans F1 hybrid sons is rescued by removing D. simulans Lhr, but not D. melanogaster Lhr, suggesting that the lethal effect results from adaptive evolution in the D. simulans lineage. It has been proposed that adaptive protein divergence in Lhr reflects antagonistic coevolution with species-specific heterochromatin sequences and that defects in LHR protein localization cause hybrid lethality. Here we present surprising results that are inconsistent with this coding-sequence-based model. Using Lhr transgenes expressed under native conditions, we find no evidence that LHR localization differs between D. melanogaster and D. simulans, nor do we find evidence that it mislocalizes in their interspecific hybrids. Rather, we demonstrate that Lhr orthologs are differentially expressed in the hybrid background, with the levels of D. simulans Lhr double that of D. melanogaster Lhr. We further show that this asymmetric expression is caused by cis-by-trans regulatory divergence of Lhr. Therefore, the non-equivalent hybrid lethal effects of Lhr orthologs can be explained by asymmetric expression of a molecular function that is shared by both orthologs and thus was presumably inherited from the ancestral allele of Lhr. We present a model whereby hybrid lethality occurs by the interaction between evolutionarily ancestral and derived alleles. PMID:22457639

  13. Gene regulatory networks modelling using a dynamic evolutionary hybrid

    PubMed Central

    2010-01-01

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

  14. Latent phenotypes pervade gene regulatory circuits

    PubMed Central

    2014-01-01

    Background Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations. Results Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit’s main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes. Conclusions Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation. PMID:24884746

  15. Latent phenotypes pervade gene regulatory circuits.

    PubMed

    Payne, Joshua L; Wagner, Andreas

    2014-05-30

    Latent phenotypes are non-adaptive byproducts of adaptive phenotypes. They exist in biological systems as different as promiscuous enzymes and genome-scale metabolic reaction networks, and can give rise to evolutionary adaptations and innovations. We know little about their prevalence in the gene expression phenotypes of regulatory circuits, important sources of evolutionary innovations. Here, we study a space of more than sixteen million three-gene model regulatory circuits, where each circuit is represented by a genotype, and has one or more functions embodied in one or more gene expression phenotypes. We find that the majority of circuits with single functions have latent expression phenotypes. Moreover, the set of circuits with a given spectrum of functions has a repertoire of latent phenotypes that is much larger than that of any one circuit. Most of this latent repertoire can be easily accessed through a series of small genetic changes that preserve a circuit's main functions. Both circuits and gene expression phenotypes that are robust to genetic change are associated with a greater number of latent phenotypes. Our observations suggest that latent phenotypes are pervasive in regulatory circuits, and may thus be an important source of evolutionary adaptations and innovations involving gene regulation.

  16. Phenotypic switching in gene regulatory networks.

    PubMed

    Thomas, Philipp; Popović, Nikola; Grima, Ramon

    2014-05-13

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

  17. Therapeutic gene editing: delivery and regulatory perspectives

    PubMed Central

    Shim, Gayong; Kim, Dongyoon; Park, Gyu Thae; Jin, Hyerim; Suh, Soo-Kyung; Oh, Yu-Kyoung

    2017-01-01

    Gene-editing technology is an emerging therapeutic modality for manipulating the eukaryotic genome by using target-sequence-specific engineered nucleases. Because of the exceptional advantages that gene-editing technology offers in facilitating the accurate correction of sequences in a genome, gene editing-based therapy is being aggressively developed as a next-generation therapeutic approach to treat a wide range of diseases. However, strategies for precise engineering and delivery of gene-editing nucleases, including zinc finger nucleases, transcription activator-like effector nuclease, and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats-associated nuclease Cas9), present major obstacles to the development of gene-editing therapies, as with other gene-targeting therapeutics. Currently, viral and non-viral vectors are being studied for the delivery of these nucleases into cells in the form of DNA, mRNA, or proteins. Clinical trials are already ongoing, and in vivo studies are actively investigating the applicability of CRISPR/Cas9 techniques. However, the concept of correcting the genome poses major concerns from a regulatory perspective, especially in terms of safety. This review addresses current research trends and delivery strategies for gene editing-based therapeutics in non-clinical and clinical settings and considers the associated regulatory issues. PMID:28392568

  18. Therapeutic gene editing: delivery and regulatory perspectives.

    PubMed

    Shim, Gayong; Kim, Dongyoon; Park, Gyu Thae; Jin, Hyerim; Suh, Soo-Kyung; Oh, Yu-Kyoung

    2017-04-10

    Gene-editing technology is an emerging therapeutic modality for manipulating the eukaryotic genome by using target-sequence-specific engineered nucleases. Because of the exceptional advantages that gene-editing technology offers in facilitating the accurate correction of sequences in a genome, gene editing-based therapy is being aggressively developed as a next-generation therapeutic approach to treat a wide range of diseases. However, strategies for precise engineering and delivery of gene-editing nucleases, including zinc finger nucleases, transcription activator-like effector nuclease, and CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats-associated nuclease Cas9), present major obstacles to the development of gene-editing therapies, as with other gene-targeting therapeutics. Currently, viral and non-viral vectors are being studied for the delivery of these nucleases into cells in the form of DNA, mRNA, or proteins. Clinical trials are already ongoing, and in vivo studies are actively investigating the applicability of CRISPR/Cas9 techniques. However, the concept of correcting the genome poses major concerns from a regulatory perspective, especially in terms of safety. This review addresses current research trends and delivery strategies for gene editing-based therapeutics in non-clinical and clinical settings and considers the associated regulatory issues.

  19. Identification of key player genes in gene regulatory networks.

    PubMed

    Nazarieh, Maryam; Wiese, Andreas; Will, Thorsten; Hamed, Mohamed; Helms, Volkhard

    2016-09-06

    Identifying the gene regulatory networks governing the workings and identity of cells is one of the main challenges in understanding processes such as cellular differentiation, reprogramming or cancerogenesis. One particular challenge is to identify the main drivers and master regulatory genes that control such cell fate transitions. In this work, we reformulate this problem as the optimization problems of computing a Minimum Dominating Set and a Minimum Connected Dominating Set for directed graphs. Both MDS and MCDS are applied to the well-studied gene regulatory networks of the model organisms E. coli and S. cerevisiae and to a pluripotency network for mouse embryonic stem cells. The results show that MCDS can capture most of the known key player genes identified so far in the model organisms. Moreover, this method suggests an additional small set of transcription factors as novel key players for governing the cell-specific gene regulatory network which can also be investigated with regard to diseases. To this aim, we investigated the ability of MCDS to define key drivers in breast cancer. The method identified many known drug targets as members of the MDS and MCDS. This paper proposes a new method to identify key player genes in gene regulatory networks. The Java implementation of the heuristic algorithm explained in this paper is available as a Cytoscape plugin at http://apps.cytoscape.org/apps/mcds . The SageMath programs for solving integer linear programming formulations used in the paper are available at https://github.com/maryamNazarieh/KeyRegulatoryGenes and as supplementary material.

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

    EPA Science Inventory

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

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

    EPA Science Inventory

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

  2. Autonomous Boolean modeling of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Socolar, Joshua; Sun, Mengyang; Cheng, Xianrui

    2014-03-01

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

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

    PubMed

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

    2016-02-10

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

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

    PubMed Central

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

    2016-01-01

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

  5. Gene regulatory logic of dopaminergic neuron differentiation

    PubMed Central

    Flames, Nuria; Hobert, Oliver

    2009-01-01

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

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

    SciTech Connect

    Fung, Elizabeth-sharon

    2008-01-01

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

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

    PubMed

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

    2010-11-29

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

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

    PubMed

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

    2017-03-10

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

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

    PubMed

    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.

  10. miR-145 mediates the antiproliferative and gene regulatory effects of vitamin D3 by directly targeting E2F3 in gastric cancer cells

    PubMed Central

    Chang, Su'e; Gao, Ling; Yang, Yang; Tong, Dongdong; Guo, Bo; Liu, Liying; Li, Zongfang; Song, Tusheng; Huang, Chen

    2015-01-01

    VitaminD3 signaling is involved in inhibiting the development and progression of gastric cancer (GC), while the active vitamin D metabolite 1-alpha,25-dihydroxyvitamin D3 (1,25(OH)2D3)-mediated gene regulatory mechanisms in GC remain unclear. We found that miR-145 is induced by 1,25(OH)2D3 in a dose- and vitamin D receptor (VDR)-dependent manner in GC cells. Inhibition of miR-145 reverses the antiproliferative effect of 1,25(OH)2D3. Furthermore, miR-145 expression was lower in tumors compared with matched normal samples and correlated with increased the E2F3 transcription factor protein staining. Overexpression of miR-145 inhibited colony formation, cell viability and induced cell arrest in S-phase in GC cells by targeting E2F3 and CDK6. miR-145 inhibition consistently abrogates the 1,25(OH)2D3-mediated suppression of E2F3, CDK6, CDK2 and CCNA2 genes. Altogether, our results indicate that miR-145 mediates the antiproliferative and gene regulatory effects of vitamin D3 in GC cells and might hold promise for prognosis and therapeutic strategies for GC treatment. PMID:25762621

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

    PubMed

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

    2014-02-01

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

  12. Generation of oscillating gene regulatory network motifs

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

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

    PubMed

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

    2008-03-01

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

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

    PubMed

    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

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

    PubMed Central

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

    2011-01-01

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

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

    PubMed

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

    2011-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

  19. Pathways and gene networks mediating the regulatory effects of cannabidiol, a nonpsychoactive cannabinoid, in autoimmune T cells.

    PubMed

    Kozela, Ewa; Juknat, Ana; Gao, Fuying; Kaushansky, Nathali; Coppola, Giovanni; Vogel, Zvi

    2016-06-03

    addition, CBD enhanced the transcription of T cell co-inhibitory molecules (Btla, Lag3, Trat1, and CD69) known to interfere with T/APC interactions. Furthermore, CBD enhanced the transcription of oxidative stress modulators with potent anti-inflammatory activity that are controlled by Nfe2l2/Nrf2 (Mt1, Mt2a, Slc30a1, Hmox1). Microarray-based gene expression profiling demonstrated that CBD exerts its immunoregulatory effects in activated memory TMOG cells via (a) suppressing proinflammatory Th17-related transcription, (b) by promoting T cell exhaustion/tolerance, (c) enhancing IFN-dependent anti-proliferative program, (d) hampering antigen presentation, and (d) inducing antioxidant milieu resolving inflammation. These findings put forward mechanism by which CBD exerts its anti-inflammatory effects as well as explain the beneficial role of CBD in pathological memory T cells and in autoimmune diseases.

  20. [Enzymatic regulatory processes in gene recombination].

    PubMed

    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.

  1. Discovering Study-Specific Gene Regulatory Networks

    PubMed Central

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

    2014-01-01

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

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

    PubMed

    Galli, Maria Cristina

    2009-11-11

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

  3. Modeling stochastic noise in gene regulatory systems.

    PubMed

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

    2014-03-01

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

  4. Modeling stochastic noise in gene regulatory systems

    PubMed Central

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

    2014-01-01

    The Master equation is considered the gold standard for modeling the stochastic mechanisms of gene regulation in molecular detail, but it is too complex to solve exactly in most cases, so approximation and simulation methods are essential. However, there is still a lack of consensus about the best way to carry these out. To help clarify the situation, we review Master equation models of gene regulation, theoretical approximations based on an expansion method due to N.G. van Kampen and R. Kubo, and simulation algorithms due to D.T. Gillespie and P. Langevin. Expansion of the Master equation shows that for systems with a single stable steady-state, the stochastic model reduces to a deterministic model in a first-order approximation. Additional theory, also due to van Kampen, describes the asymptotic behavior of multistable systems. To support and illustrate the theory and provide further insight into the complex behavior of multistable systems, we perform a detailed simulation study comparing the various approximation and simulation methods applied to synthetic gene regulatory systems with various qualitative characteristics. The simulation studies show that for large stochastic systems with a single steady-state, deterministic models are quite accurate, since the probability distribution of the solution has a single peak tracking the deterministic trajectory whose variance is inversely proportional to the system size. In multistable stochastic systems, large fluctuations can cause individual trajectories to escape from the domain of attraction of one steady-state and be attracted to another, so the system eventually reaches a multimodal probability distribution in which all stable steady-states are represented proportional to their relative stability. However, since the escape time scales exponentially with system size, this process can take a very long time in large systems. PMID:25632368

  5. Modeling stochasticity and variability in gene regulatory networks.

    PubMed

    Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Arat, Seda; Laubenbacher, Reinhard

    2012-06-06

    Modeling stochasticity in gene regulatory networks is an important and complex problem in molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This article contributes an approach as an alternative to these classical settings. Within the discrete paradigm, where genes, proteins, and other molecular components of gene regulatory networks are modeled as discrete variables and are assigned as logical rules describing their regulation through interactions with other components. Stochasticity is modeled at the biological function level under the assumption that even if the expression levels of the input nodes of an update rule guarantee activation or degradation there is a probability that the process will not occur due to stochastic effects. This approach allows a finer analysis of discrete models and provides a natural setup for cell population simulations to study cell-to-cell variability. We applied our methods to two of the most studied regulatory networks, the outcome of lambda phage infection of bacteria and the p53-mdm2 complex.

  6. Modeling stochasticity and variability in gene regulatory networks

    PubMed Central

    2012-01-01

    Modeling stochasticity in gene regulatory networks is an important and complex problem in molecular systems biology. To elucidate intrinsic noise, several modeling strategies such as the Gillespie algorithm have been used successfully. This article contributes an approach as an alternative to these classical settings. Within the discrete paradigm, where genes, proteins, and other molecular components of gene regulatory networks are modeled as discrete variables and are assigned as logical rules describing their regulation through interactions with other components. Stochasticity is modeled at the biological function level under the assumption that even if the expression levels of the input nodes of an update rule guarantee activation or degradation there is a probability that the process will not occur due to stochastic effects. This approach allows a finer analysis of discrete models and provides a natural setup for cell population simulations to study cell-to-cell variability. We applied our methods to two of the most studied regulatory networks, the outcome of lambda phage infection of bacteria and the p53-mdm2 complex. PMID:22673395

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

    PubMed

    Watson, Emma; Walhout, Albertha J M

    2014-10-01

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

  8. Effect of ration size on fillet fatty acid composition, phospholipid allostasis and mRNA expression patterns of lipid regulatory genes in gilthead sea bream (Sparus aurata).

    PubMed

    Benedito-Palos, Laura; Calduch-Giner, Josep A; Ballester-Lozano, Gabriel F; Pérez-Sánchez, Jaume

    2013-04-14

    The effect of ration size on muscle fatty acid (FA) composition and mRNA expression levels of key regulatory enzymes of lipid and lipoprotein metabolism have been addressed in juveniles of gilthead sea bream fed a practical diet over the course of an 11-week trial. The experimental setup included three feeding levels: (i) full ration until visual satiety, (ii) 70 % of satiation and (iii) 70 % of satiation with the last 2 weeks at the maintenance ration. Feed restriction reduced lipid content of whole body by 30 % and that of fillet by 50 %. In this scenario, the FA composition of fillet TAG was not altered by ration size, whereas that of phospholipids was largely modified with a higher retention of arachidonic acid and DHA. The mRNA transcript levels of lysophosphatidylcholine acyltransferases, phosphatidylethanolamine N-methyltransferase and FA desaturase 2 were not regulated by ration size in the present experimental model. In contrast, mRNA levels of stearoyl-CoA desaturases were markedly down-regulated by feed restriction. An opposite trend was found for a muscle-specific lipoprotein lipase, which is exclusive of fish lineage. Several upstream regulatory transcriptions were also assessed, although nutritionally mediated changes in mRNA transcripts were almost reduced to PPARα and β, which might act in a counter-regulatory way on lipolysis and lipogenic pathways. This gene expression pattern contributes to the construction of a panel of biomarkers to direct marine fish production towards muscle lean phenotypes with increased retentions of long-chain PUFA.

  9. Identification of cis-regulatory mutations generating de novo edges in personalized cancer gene regulatory networks.

    PubMed

    Kalender Atak, Zeynep; Imrichova, Hana; Svetlichnyy, Dmitry; Hulselmans, Gert; Christiaens, Valerie; Reumers, Joke; Ceulemans, Hugo; Aerts, Stein

    2017-08-30

    The identification of functional non-coding mutations is a key challenge in the field of genomics. Here we introduce μ-cisTarget to filter, annotate and prioritize cis-regulatory mutations based on their putative effect on the underlying "personal" gene regulatory network. We validated μ-cisTarget by re-analyzing the TAL1 and LMO1 enhancer mutations in T-ALL, and the TERT promoter mutation in melanoma. Next, we re-sequenced the full genomes of ten cancer cell lines and used matched transcriptome data and motif discovery to identify master regulators with de novo binding sites that result in the up-regulation of nearby oncogenic drivers. μ-cisTarget is available from http://mucistarget.aertslab.org .

  10. An internal regulatory element controls troponin I gene expression

    SciTech Connect

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

    1989-04-01

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

  11. Intersecting transcription networks constrain gene regulatory evolution

    PubMed Central

    Sorrells, Trevor R; Booth, Lauren N; Tuch, Brian B; Johnson, Alexander D

    2015-01-01

    Epistasis—the non-additive interactions between different genetic loci—constrains evolutionary pathways, blocking some and permitting others1–8. For biological networks such as transcription circuits, the nature of these constraints and their consequences are largely unknown. Here we describe the evolutionary pathways of a transcription network that controls the response to mating pheromone in yeasts9. A component of this network, the transcription regulator Ste12, has evolved two different modes of binding to a set of its target genes. In one group of species, Ste12 binds to specific DNA binding sites, while in another lineage it occupies DNA indirectly, relying on a second transcription regulator to recognize DNA. We show, through the construction of various possible evolutionary intermediates, that evolution of the direct mode of DNA binding was not directly accessible to the ancestor. Instead, it was contingent on a lineage-specific change to an overlapping transcription network with a different function, the specification of cell type. These results show that analyzing and predicting the evolution of cis-regulatory regions requires an understanding of their positions in overlapping networks, as this placement constrains the available evolutionary pathways. PMID:26153861

  12. Toward an orofacial gene regulatory network.

    PubMed

    Kousa, Youssef A; Schutte, Brian C

    2016-03-01

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

  13. Chaotic Motifs in Gene Regulatory Networks

    PubMed Central

    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. PMID:22792171

  14. Chaotic motifs in gene regulatory networks.

    PubMed

    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.

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

    PubMed

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

    2016-08-01

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

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

    PubMed

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

    2015-11-20

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

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

    PubMed

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

    2017-02-27

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

  18. LitR Is a Repressor of syp Genes and Has a Temperature-Sensitive Regulatory Effect on Biofilm Formation and Colony Morphology in Vibrio (Aliivibrio) salmonicida

    PubMed Central

    Bjelland, Ane Mohn; Ronessen, Maria; Robertsen, Espen; Willassen, Nils Peder

    2014-01-01

    Vibrio (Aliivibrio) salmonicida is the etiological agent of cold water vibriosis, a disease in farmed Atlantic salmon (Salmo salar) that is kept under control due to an effective vaccine. A seawater temperature below 12°C is normally required for disease development. Quorum sensing (QS) is a cell density-regulated communication system that bacteria use to coordinate activities involved in colonization and pathogenesis, and we have previously shown that inactivation of the QS master regulator LitR attenuates the V. salmonicida strain LFI1238 in a fish model. We show here that strain LFI1238 and a panel of naturally occurring V. salmonicida strains are poor biofilm producers. Inactivation of litR in the LFI1238 strain enhances medium- and temperature-dependent adhesion, rugose colony morphology, and biofilm formation. Chemical treatment and electron microscopy of the biofilm identified an extracellular matrix consisting mainly of a fibrous network, proteins, and polysaccharides. Further, by microarray analysis of planktonic and biofilm cells, we identified a number of genes regulated by LitR and, among these, were homologues of the Vibrio fischeri symbiosis polysaccharide (syp) genes. The syp genes were regulated by LitR in both planktonic and biofilm lifestyle analyses. Disruption of syp genes in the V. salmonicida ΔlitR mutant alleviated adhesion, rugose colony morphology, and biofilm formation. Hence, LitR is a repressor of syp transcription that is necessary for expression of the phenotypes examined. The regulatory effect of LitR on colony morphology and biofilm formation is temperature sensitive and weak or absent at temperatures above the bacterium's upper threshold for pathogenicity. PMID:24973072

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

    PubMed

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

    2017-01-02

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

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

    PubMed

    Banf, Michael; Rhee, Seung Y

    2017-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed

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

    2014-01-25

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

  3. Perturbation analysis analyzed - Mathematical modeling of intact and perturbed gene regulatory circuits for animal development

    PubMed Central

    de-Leon, Smadar Ben-Tabou

    2010-01-01

    Gene regulatory networks for animal development are the underlying mechanisms controlling cell fate specification and differentiation. The architecture of gene regulatory circuits determines their information processing properties and their developmental function. It is a major task to derive realistic network models from exceedingly advanced high throughput experimental data. Here we use mathematical modeling to study the dynamics of gene regulatory circuits to advance the ability to infer regulatory connections and logic function from experimental data. This study is guided by experimental methodologies that are commonly used to study gene regulatory networks that control cell fate specification. We study the effect of a perturbation of an input on the level of its downstream genes and compare between the cis-regulatory execution of OR and AND logics. Circuits that initiate gene activation and circuits that lock on the expression of genes are analyzed. The model improves our ability to analyze experimental data and construct from it the network topology. The model also illuminates information processing properties of gene regulatory circuits for animal development. PMID:20599898

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

    PubMed

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

    2010-01-01

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

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

    PubMed

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

    2014-01-01

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

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

    PubMed Central

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

    2011-01-01

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

  7. Phenotypic plasticity can facilitate adaptive evolution in gene regulatory circuits

    PubMed Central

    2011-01-01

    Background Many important evolutionary adaptations originate in the modification of gene regulatory circuits to produce new gene activity phenotypes. How do evolving populations sift through an astronomical number of circuits to find circuits with new adaptive phenotypes? The answer may often involve phenotypic plasticity. Phenotypic plasticity allows a genotype to produce different - alternative - phenotypes after non-genetic perturbations that include gene expression noise, environmental change, or epigenetic modification. Results We here analyze a well-studied model of gene regulatory circuits. A circuit's genotype encodes the regulatory interactions among circuit genes, and its phenotype corresponds to a stable gene activity pattern the circuit forms. For this model, we study how genotypes are arranged in genotype space, where the distance between two genotypes reflects the number of regulatory mutations that set those genotypes apart. Specifically, we address whether this arrangement favors adaptive evolution mediated by plasticity. We find that plasticity facilitates the origin of genotypes that produce a new phenotype in response to non-genetic perturbations. We also find that selection can then stabilize the new phenotype genetically, allowing it to become a circuit's dominant gene expression phenotype. These are generic properties of the circuits we study here. Conclusions Taken together, our observations suggest that phenotypic plasticity frequently facilitates the evolution of novel beneficial gene activity patterns in gene regulatory circuits. PMID:21211007

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

    PubMed

    Ben-Tabou de-Leon, Smadar

    2016-01-01

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

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

    PubMed Central

    Tian, Dechao; Gu, Quanquan; Ma, Jian

    2016-01-01

    Gene regulatory networks (GRNs) are highly dynamic among different tissue types. Identifying tissue-specific gene regulation is critically important to understand gene function in a particular cellular context. Graphical models have been used to estimate GRN from gene expression data to distinguish direct interactions from indirect associations. However, most existing methods estimate GRN for a specific cell/tissue type or in a tissue-naive way, or do not specifically focus on network rewiring between different tissues. Here, we describe a new method called Latent Differential Graphical Model (LDGM). The motivation of our method is to estimate the differential network between two tissue types directly without inferring the network for individual tissues, which has the advantage of utilizing much smaller sample size to achieve reliable differential network estimation. Our simulation results demonstrated that LDGM consistently outperforms other Gaussian graphical model based methods. We further evaluated LDGM by applying to the brain and blood gene expression data from the GTEx consortium. We also applied LDGM to identify network rewiring between cancer subtypes using the TCGA breast cancer samples. Our results suggest that LDGM is an effective method to infer differential network using high-throughput gene expression data to identify GRN dynamics among different cellular conditions. PMID:27378774

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

    PubMed

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

    2015-10-15

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

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

    PubMed Central

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

    2015-01-01

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

  12. Regulatory divergence between parental alleles determines gene expression patterns in hybrids.

    PubMed

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

    2015-03-29

    Both hybridization and allopolyploidization generate novel phenotypes by conciliating divergent genomes and regulatory networks in the same cellular context. To understand the rewiring of gene expression in hybrids, the total expression of 21,025 genes and the allele-specific expression of over 11,000 genes were quantified in interspecific hybrids and their parental species, Coffea canephora and Coffea eugenioides using RNA-seq technology. Between parental species, cis- and trans-regulatory divergences affected around 32% and 35% of analyzed genes, respectively, with nearly 17% of them showing both. The relative importance of trans-regulatory divergences between both species could be related to their low genetic divergence and perennial habit. In hybrids, among divergently expressed genes between parental species and hybrids, 77% was expressed like one parent (expression level dominance), including 65% like C. eugenioides. Gene expression was shown to result from the expression of both alleles affected by intertwined parental trans-regulatory factors. A strong impact of C. eugenioides trans-regulatory factors on the upregulation of C. canephora alleles was revealed. The gene expression patterns appeared determined by complex combinations of cis- and trans-regulatory divergences. In particular, the observed biased expression level dominance seemed to be derived from the asymmetric effects of trans-regulatory parental factors on regulation of alleles. More generally, this study illustrates the effects of divergent trans-regulatory parental factors on the gene expression pattern in hybrids. The characteristics of the transcriptional response to hybridization appear to be determined by the compatibility of gene regulatory networks and therefore depend on genetic divergences between the parental species and their evolutionary history. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

  13. Implications of functional similarity for gene regulatory interactions

    PubMed Central

    Glass, Kimberly; Ott, Edward; Losert, Wolfgang; Girvan, Michelle

    2012-01-01

    If one gene regulates another, those two genes are likely to be involved in many of the same biological functions. Conversely, shared biological function may be suggestive of the existence and nature of a regulatory interaction. With this in mind, we develop a measure of functional similarity between genes based on annotations made to the Gene Ontology in which the magnitude of their functional relationship is also indicative of a regulatory relationship. In contrast to other measures that have previously been used to quantify the functional similarity between genes, our measure scales the strength of any shared functional annotation by the frequency of that function's appearance across the entire set of annotations. We apply our method to both Escherichia coli and Saccharomyces cerevisiae gene annotations and find that the strength of our scaled similarity measure is more predictive of known regulatory interactions than previously published measures of functional similarity. In addition, we observe that the strength of the scaled similarity measure is correlated with the structural importance of links in the known regulatory network. By contrast, other measures of functional similarity are not indicative of any structural importance in the regulatory network. We therefore conclude that adequately adjusting for the frequency of shared biological functions is important in the construction of a functional similarity measure aimed at elucidating the existence and nature of regulatory interactions. We also compare the performance of the scaled similarity with a high-throughput method for determining regulatory interactions from gene expression data and observe that the ontology-based approach identifies a different subset of regulatory interactions compared with the gene expression approach. We show that combining predictions from the scaled similarity with those from the reconstruction algorithm leads to a significant improvement in the accuracy of the reconstructed

  14. Molecular characterization of a maize regulatory gene

    SciTech Connect

    Wessler, S.R.

    1991-12-01

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

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

    PubMed

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

    2003-06-01

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

  16. Evolutionary Conservation of Regulatory Elements in Vertebrate Hox Gene Clusters

    PubMed Central

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

    2003-01-01

    Comparisons of DNA sequences among evolutionarily distantly related genomes permit identification of conserved functional regions in noncoding DNA. Hox genes are highly conserved in vertebrates, occur in clusters, and are uninterrupted by other genes. We aligned (PipMaker) the nucleotide sequences of the HoxA clusters of tilapia, pufferfish, striped bass, zebrafish, horn shark, human, and mouse, which are separated by approximately 500 million years of evolution. In support of our approach, several identified putative regulatory elements known to regulate the expression of Hox genes were recovered. The majority of the newly identified putative regulatory elements contain short fragments that are almost completely conserved and are identical to known binding sites for regulatory proteins (Transfac database). The regulatory intergenic regions located between the genes that are expressed most anteriorly in the embryo are longer and apparently more evolutionarily conserved than those at the other end of Hox clusters. Different presumed regulatory sequences are retained in either the Aα or Aβ duplicated Hox clusters in the fish lineages. This suggests that the conserved elements are involved in different gene regulatory networks and supports the duplication-deletion-complementation model of functional divergence of duplicated genes. PMID:12799348

  17. Down-regulatory effect of Thymus vulgaris L. on growth and Tri4 gene expression in Fusarium oxysporum strains.

    PubMed

    Divband, Kolsum; Shokri, Hojjatollah; Khosravi, Ali Reza

    2017-03-01

    The aims of this study were to evaluate the efficacy of Thymus vulgaris (T. vulgaris) essential oil on the fungal growth and Tri4 gene expression in Fusarium oxysporum (F. oxysporum) strains. The oil was obtained by water-distillation using a Clevenger-type system. The chemical composition of the essential oil was obtained by gas chromatography- mass spectroscopy (GC-MS) and by retention indices. The antifungal activity was evaluated by broth microdilution assay. A quantitative real time RT-PCR (qRT-PCR) assay was also developed specific for F. oxysporum on the basis of trichothecene biosynthetic gene, Tri4, which allowed discrimination from F. oxysporum. Results showed thymol (32.67%) and p-cymene (16.68%) as the main components of T. vulgaris. Minimum inhibitory concentration (MIC) values varied from 5 to 20 μg/ml with T. vulgaris (mean: 10.50 μg/ml), while minimum fungicidal concentration (MFC) values ranged from 8 to 30 μg/ml with mean value of 16.20 μg/ml qRT-PCR results revealed a downregulation from 4.04 to 6.27 fold of Tri4 gene expression of the fungi exposed to T. vulgaris essential oil. The results suggest that T. vulgaris oil can be considered potential alternative natural fungicide to the synthetic chemicals that are currently used to prevent and control seed-borne diseases. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed

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

    2015-01-01

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

  19. Regulatory Effects of Programmed Cell Death 4 (PDCD4) Protein in Interferon (IFN)-Stimulated Gene Expression and Generation of Type I IFN Responses

    PubMed Central

    Kroczynska, Barbara; Sharma, Bhumika; Eklund, Elizabeth A.; Fish, Eleanor N.

    2012-01-01

    The precise mechanisms by which the activation of interferon (IFN) receptors (IFNRs) ultimately controls mRNA translation of specific target genes to induce IFN-dependent biological responses remain ill defined. We provide evidence that IFN-α induces phosphorylation of programmed cell death 4 (PDCD4) protein on Ser67. This IFN-α-dependent phosphorylation is mediated by either the p70 S6 kinase (S6K) or the p90 ribosomal protein S6K (RSK) in a cell-type-specific manner. IFN-dependent phosphorylation of PDCD4 results in downregulation of PDCD4 protein levels as the phosphorylated form of PDCD4 interacts with the ubiquitin ligase β-TRCP (β-transducin repeat-containing protein) and undergoes degradation. This process facilitates IFN-induced eukaryotic translation initiation factor 4A (eIF4A) activity and binding to translation initiation factor eIF4G to promote mRNA translation. Our data establish that PDCD4 degradation ultimately facilitates expression of several ISG protein products that play important roles in the generation of IFN responses, including IFN-stimulated gene 15 (ISG15), p21WAF1/CIP1, and Schlafen 5 (SLFN5). Moreover, engagement of the RSK/PDCD4 pathway by the type I IFNR is required for the suppressive effects of IFN-α on normal CD34+ hematopoietic precursors and for antileukemic effects in vitro. Altogether, these findings provide evidence for a unique function of PDCD4 in the type I IFN system and indicate a key regulatory role for this protein in mRNA translation of ISGs and control of IFN responses. PMID:22586265

  20. Regulatory effects of programmed cell death 4 (PDCD4) protein in interferon (IFN)-stimulated gene expression and generation of type I IFN responses.

    PubMed

    Kroczynska, Barbara; Sharma, Bhumika; Eklund, Elizabeth A; Fish, Eleanor N; Platanias, Leonidas C

    2012-07-01

    The precise mechanisms by which the activation of interferon (IFN) receptors (IFNRs) ultimately controls mRNA translation of specific target genes to induce IFN-dependent biological responses remain ill defined. We provide evidence that IFN-α induces phosphorylation of programmed cell death 4 (PDCD4) protein on Ser67. This IFN-α-dependent phosphorylation is mediated by either the p70 S6 kinase (S6K) or the p90 ribosomal protein S6K (RSK) in a cell-type-specific manner. IFN-dependent phosphorylation of PDCD4 results in downregulation of PDCD4 protein levels as the phosphorylated form of PDCD4 interacts with the ubiquitin ligase β-TRCP (β-transducin repeat-containing protein) and undergoes degradation. This process facilitates IFN-induced eukaryotic translation initiation factor 4A (eIF4A) activity and binding to translation initiation factor eIF4G to promote mRNA translation. Our data establish that PDCD4 degradation ultimately facilitates expression of several ISG protein products that play important roles in the generation of IFN responses, including IFN-stimulated gene 15 (ISG15), p21(WAF1/CIP1), and Schlafen 5 (SLFN5). Moreover, engagement of the RSK/PDCD4 pathway by the type I IFNR is required for the suppressive effects of IFN-α on normal CD34(+) hematopoietic precursors and for antileukemic effects in vitro. Altogether, these findings provide evidence for a unique function of PDCD4 in the type I IFN system and indicate a key regulatory role for this protein in mRNA translation of ISGs and control of IFN responses.

  1. Steroidogenic acute regulatory protein (StAR) gene expression construct: Development, nanodelivery and effect on reproduction in air-breathing catfish, Clarias batrachus.

    PubMed

    Rathor, Pravesh Kumar; Bhat, Irfan Ahmad; Rather, Mohd Ashraf; Gireesh-Babu, Pathakota; Kumar, Kundan; Purayil, Suresh Babu Padinhate; Sharma, Rupam

    2017-11-01

    Steroidogenic acute regulatory protein (StAR) is responsible for the relocation of cholesterol across mitochondrial membrane in vertebrates and is, therefore, a key factor in regulating the rate and timing of steroidogenesis. In the present study, we developed chitosan nanoparticle (CNP) conjugated StAR gene construct (CNP-pcDNA4-StAR) in a eukaryotic expression vector, pcDNA4/HisMax A. CNPs of 135.4nm diameter, 26.7mV zeta potential and 0.381 polydispersity index were used for conjugation. The loading efficiency (LE) of pcDNA4-StAR construct with CNPs was found to be 86%. After the 24h of intramuscular injection, the CNP-pcDNA4-StAR plasmid could be detected from testis, brain, kidney and muscle tissues of Clarias batrachus. The transcript levels of important reproductive genes viz. cyp11a1, cyp17a1, 3β-hsd, 17β-hsd and cyp19a1 in CNP-pcDNA4-StAR treated group were initially low up to 24h, but significantly increased subsequently up to 120h. In naked pcDNA4-StAR treated group, the mRNA level of 3β-hsd, 17β-hsd and cyp19a1 increased initially up to 24h, while cyp11a1 and cyp17a1 increased up to 48h and then started declining. Similar results were obtained for 11-Ketotestosterone and 17β-estradiol. The results indicate relatively long lasting effects of nano-conjugated construct compared to the construct alone. Furthermore, the histopathology of gonads and liver authenticates its possible role in the gonadal development in fish without any adverse effect. Copyright © 2017 Elsevier B.V. All rights reserved.

  2. A cis-Regulatory Signature for Chordate Anterior Neuroectodermal Genes

    PubMed Central

    Christiaen, Lionel; Joly, Jean-Stéphane

    2010-01-01

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

  3. The companions: regulatory T cells and gene therapy

    PubMed Central

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

    2009-01-01

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

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

    PubMed

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

    2007-10-01

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

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

    PubMed Central

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

    2007-01-01

    We report evidence for a mechanism for the maintenance of long-range conserved synteny across vertebrate genomes. We found the largest mammal-teleost conserved chromosomal segments to be spanned by highly conserved noncoding elements (HCNEs), their developmental regulatory target genes, and phylogenetically and functionally unrelated “bystander” genes. Bystander genes are not specifically under the control of the regulatory elements that drive the target genes and are expressed in patterns that are different from those of the target genes. Reporter insertions distal to zebrafish developmental regulatory genes pax6.1/2, rx3, id1, and fgf8 and miRNA genes mirn9-1 and mirn9-5 recapitulate the expression patterns of these genes even if located inside or beyond bystander genes, suggesting that the regulatory domain of a developmental regulatory gene can extend into and beyond adjacent transcriptional units. We termed these chromosomal segments genomic regulatory blocks (GRBs). After whole genome duplication in teleosts, GRBs, including HCNEs and target genes, were often maintained in both copies, while bystander genes were typically lost from one GRB, strongly suggesting that evolutionary pressure acts to keep the single-copy GRBs of higher vertebrates intact. We show that loss of bystander genes and other mutational events suffered by duplicated GRBs in teleost genomes permits target gene identification and HCNE/target gene assignment. These findings explain the absence of evolutionary breakpoints from large vertebrate chromosomal segments and will aid in the recognition of position effect mutations within human GRBs. PMID:17387144

  6. Novel Pd(II)-salen complexes showing high in vitro anti-proliferative effects against human hepatoma cancer by modulating specific regulatory genes.

    PubMed

    Azam, Mohammad; Hussain, Zahid; Warad, Ismail; Al-Resayes, Saud I; Khan, Mohd Shahnawaz; Shakir, Mohammad; Trzesowska-Kruszynska, Agata; Kruszynski, Rafal

    2012-09-21

    We have reported the synthesis of a novel salen ligand and its mononuclear Pd-salen complexes derived from 2-{[2-hydroxy-3-{[(E)-(2-hydroxyphenyl)methylidene]amino}propyl)imino]methyl}phenol. The newly synthesized and isolated Pd(II) complexes have been identified and fully characterized by various physico-chemical studies viz., elemental analyses, IR, UV-Vis, (1)H, (13)C NMR spectroscopy, electron spray ionization mass spectrometry (ESI-MS) and TGA/DTA studies. The molecular structure of the salen ligand has been ascertained by single-crystal XRD and it is coordinated to Pd(II) ion through two nitrogen and two oxygen atoms. The UV-Vis data clearly suggest a square-planar environment around both the Pd(II) ions. The DNA binding studies of the synthesized compounds has been investigated by electron spectroscopy and fluorescence measurements. The results suggest that Pd(II) complexes bind to DNA strongly as compared to the free ligand. The free salen ligand and its Pd(II) complexes have also been tested against human hepatoma cancer cell line (Huh7) and results manifested exceptional anti-proliferative effects of the Pd(II) complexes. The anti-proliferative activity of Pd(II) complexes has been modulated by specific regulatory genes.

  7. The molecular and gene regulatory signature of a neuron

    PubMed Central

    Hobert, Oliver; Carrera, Inés; Stefanakis, Nikolaos

    2010-01-01

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

  8. Estimating Gene Regulatory Networks with pandaR.

    PubMed

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

    2017-03-11

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

  9. Time-Delayed Models of Gene Regulatory Networks

    PubMed Central

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

    2015-01-01

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

  10. Systems Approaches to Identifying Gene Regulatory Networks in Plants

    PubMed Central

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

    2009-01-01

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

  11. Construction of gene regulatory networks using biclustering and bayesian networks

    PubMed Central

    2011-01-01

    Background Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling. Results In this paper, we develop a biclustering function enrichment analysis toolbox (BicAT-plus) to study the effect of biclustering in reducing data dimensions. The network generated from our system was validated via available interaction databases and was compared with previous methods. The results revealed the performance of our proposed method. Conclusions Because of the sparse nature of GRNs, the results of biclustering techniques differ significantly from those of previous methods. PMID:22018164

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

    PubMed Central

    Benecke, Arndt

    2008-01-01

    Spatiotemporal control of gene expression is fundamental to multicellular life. Despite prodigious efforts, the encoding of gene expression regulation in eukaryotes is not understood. Gene expression analyses nourish the hope to reverse engineer effector-target gene networks using inference techniques. Inference from noisy and circumstantial data relies on using robust models with few parameters for the underlying mechanisms. However, a systematic path to gene regulatory network reverse engineering from functional genomics data is still impeded by fundamental problems. Recently, Johannes Berg from the Theoretical Physics Institute of Cologne University has made two remarkable contributions that significantly advance the gene regulatory network inference problem. Berg, who uses gene expression data from yeast, has demonstrated a nonequilibrium regime for mRNA concentration dynamics and was able to map the gene regulatory process upon simple stochastic systems driven out of equilibrium. The impact of his demonstration is twofold, affecting both the understanding of the operational constraints under which transcription occurs and the capacity to extract relevant information from highly time-resolved expression data. Berg has used his observation to predict target genes of selected transcription factors, and thereby, in principle, demonstrated applicability of his out of equilibrium statistical mechanics approach to the gene network inference problem. PMID:19404429

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

    PubMed

    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.

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

    SciTech Connect

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

    2003-12-31

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

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

    PubMed Central

    2012-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar; hide

    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

  18. Portrait of Candida Species Biofilm Regulatory Network Genes.

    PubMed

    Araújo, Daniela; Henriques, Mariana; Silva, Sónia

    2017-01-01

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

  19. Effects of transforming growth factor beta-1 on growth-regulatory genes in tumour-derived human oral keratinocytes.

    PubMed Central

    Paterson, I. C.; Patel, V.; Sandy, J. R.; Prime, S. S.; Yeudall, W. A.

    1995-01-01

    This study examined the effect of transforming growth factor beta-1 (TGF-beta 1) on c-myc, RB1, junB and p53 expression together with pRb phosphorylation, in carcinoma-derived and normal human oral keratinocytes with a range of inhibitory responses to this ligand. Amplification of c-myc was observed in eight of eight tumour-derived cell lines and resulted in corresponding mRNA expression. The down-regulation of c-myc expression by TGF-beta 1 predominantly reflected growth inhibition by TGF-beta 1, but in two of eight tumour-derived cell lines which were partially responsive to TGF-beta 1 c-myc expression was unaltered by this ligand. While RB1 mRNA levels were unaltered by TGF-beta 1, the ligand caused the accumulation of the underphosphorylated form of the Rb protein in all cells irrespective of TGF-beta 1-induced growth arrest. junB expression was up-regulated by TGF-beta 1 in cells with a range of growth inhibitory responses. All cells contained mutant p53. TGF-beta 1 did not affect p53 mRNA expression in both tumour-derived and normal keratinocytes and there was no alteration in p53 protein levels in keratinocytes expressing stable p53 protein following TGF-beta 1 treatment. The data indicate that TGF-beta-induced growth control can exist independently of the presence of mutant p53 and the control of Rb phosphorylation and c-myc down-regulation. It may be that TGF-beta growth inhibition occurs via multiple mechanisms and that the loss of one pathway during tumour progression does not necessarily result in the abrogation of TGF-beta-induced growth control. Images Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:7547241

  20. A Maize Gene Regulatory Network for Phenolic Metabolism.

    PubMed

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

    2017-03-06

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

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

    PubMed

    Peter, Isabelle S; Davidson, Eric H

    2011-05-29

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

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

    PubMed

    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.

  3. Gene Regulatory Evolution During Speciation in a Songbird

    PubMed Central

    Davidson, John H.; Balakrishnan, Christopher N.

    2016-01-01

    Over the last decade, tremendous progress has been made toward a comparative understanding of gene regulatory evolution. However, we know little about how gene regulation evolves in birds, and how divergent genomes interact in their hybrids. Because of the unique features of birds – female heterogamety, a highly conserved karyotype, and the slow evolution of reproductive incompatibilities – an understanding of regulatory evolution in birds is critical to a comprehensive understanding of regulatory evolution and its implications for speciation. Using a novel complement of analyses of replicated RNA-seq libraries, we demonstrate abundant divergence in brain gene expression between zebra finch (Taeniopygia guttata) subspecies. By comparing parental populations and their F1 hybrids, we also show that gene misexpression is relatively rare among brain-expressed transcripts in male birds. If this pattern is consistent across tissues and sexes, it may partially explain the slow buildup of postzygotic reproductive isolation observed in birds relative to other taxa. Although we expected that the action of genetic drift on the island-dwelling zebra finch subspecies would be manifested in a higher rate of trans regulatory divergence, we found that most divergence was in cis regulation, following a pattern commonly observed in other taxa. Thus, our study highlights both unique and shared features of avian regulatory evolution. PMID:26976438

  4. Dynamics of gene regulatory networks with cell division cycle

    NASA Astrophysics Data System (ADS)

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

    2004-07-01

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

  5. Gene regulatory networks elucidating huanglongbing disease mechanisms.

    PubMed

    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.

  6. Evolutionary conservation of the eumetazoan gene regulatory landscape

    PubMed Central

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

    2014-01-01

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

  7. Dynamic integration of splicing within gene regulatory pathways

    PubMed Central

    Braunschweig, Ulrich; Gueroussov, Serge; Plocik, Alex; Graveley, Brenton R.; Blencowe, Benjamin J.

    2013-01-01

    Precursor mRNA splicing is one of the most highly regulated processes in metazoan species. In addition to generating vast repertoires of RNAs and proteins, splicing has a profound impact on other gene regulatory layers, including mRNA transcription, turnover, transport and translation. Conversely, factors regulating chromatin and transcription complexes impact the splicing process. This extensive cross-talk between gene regulatory layers takes advantage of dynamic spatial, physical and temporal organizational properties of the cell nucleus, and further emphasizes the importance of developing a multidimensional understanding of splicing control. PMID:23498935

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

    PubMed

    Nicholson, Charles; Goodwin, Leslie; Clark, Corey

    2017-01-01

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

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

    PubMed

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

    2015-10-01

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

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

    PubMed

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

    2009-01-01

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

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

    PubMed

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

    2014-07-01

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

  12. Enhancer Variants Synergistically Drive Dysfunction of a Gene Regulatory Network In Hirschsprung Disease

    SciTech Connect

    Chatterjee, Sumantra; Kapoor, Ashish; Akiyama, Jennifer A.; Auer, Dallas R.; Lee, Dongwon; Gabriel, Stacey; Berrios, Courtney; Pennacchio, Len A.; Chakravarti, Aravinda

    2016-10-01

    Common sequence variants in cis-regulatory elements (CREs) are suspected etiological causes of complex disorders. We previously identified an intronic enhancer variant in the RET gene disrupting SOX10 binding and increasing Hirschsprung disease (HSCR) risk 4-fold. We now show that two other functionally independent CRE variants, one binding Gata2 and the other binding Rarb, also reduce Ret expression and increase risk 2- and 1.7-fold. By studying human and mouse fetal gut tissues and cell lines, we demonstrate that reduced RET expression propagates throughout its gene regulatory network, exerting effects on both its positive and negative feedback components. We also provide evidence that the presence of a combination of CRE variants synergistically reduces RET expression and its effects throughout the GRN. These studies show how the effects of functionally independent non-coding variants in a coordinated gene regulatory network amplify their individually small effects, providing a model for complex disorders.

  13. The Effectiveness of Regulatory Disclosure Policies

    ERIC Educational Resources Information Center

    Weil, David; Fung, Archon; Graham, Mary; Fagotto, Elena

    2006-01-01

    Regulatory transparency--mandatory disclosure of information by private or public institutions with a regulatory intent--has become an important frontier of government innovation. This paper assesses the effectiveness of such transparency systems by examining the design and impact of financial disclosure, nutritional labeling, workplace hazard…

  14. The Effectiveness of Regulatory Disclosure Policies

    ERIC Educational Resources Information Center

    Weil, David; Fung, Archon; Graham, Mary; Fagotto, Elena

    2006-01-01

    Regulatory transparency--mandatory disclosure of information by private or public institutions with a regulatory intent--has become an important frontier of government innovation. This paper assesses the effectiveness of such transparency systems by examining the design and impact of financial disclosure, nutritional labeling, workplace hazard…

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

    PubMed

    Li, Li; Yang, Yang; Xue, Lei

    2010-02-01

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

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

    PubMed

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

    2013-05-01

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

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

    PubMed

    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.

  18. Rapid Male-Specific Regulatory Divergence and Down Regulation of Spermatogenesis Genes in Drosophila Species Hybrids

    PubMed Central

    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. PMID:23593487

  19. Charting gene regulatory networks: strategies, challenges and perspectives

    PubMed Central

    2004-01-01

    One of the foremost challenges in the post-genomic era will be to chart the gene regulatory networks of cells, including aspects such as genome annotation, identification of cis-regulatory elements and transcription factors, information on protein–DNA and protein–protein interactions, and data mining and integration. Some of these broad sets of data have already been assembled for building networks of gene regulation. Even though these datasets are still far from comprehensive, and the approach faces many important and difficult challenges, some strategies have begun to make connections between disparate regulatory events and to foster new hypotheses. In this article we review several different genomics and proteomics technologies, and present bioinformatics methods for exploring these data in order to make novel discoveries. PMID:15080794

  20. Combinatorial Gene Regulatory Functions Underlie Ultraconserved Elements in Drosophila

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-09-01

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

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

    PubMed

    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.

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

    PubMed Central

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

    2012-01-01

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

  4. Gene regulatory networks in the early ascidian embryo.

    PubMed

    Satou, Yutaka; Satoh, Nori; Imai, Kaoru S

    2009-04-01

    Ascidians, or sea squirts, are tunicates that diverged from the vertebrate lineage early in the chordate evolution. The compact and simple organization of the ascidian genome makes this organism an ideal model system for analyzing gene regulatory networks in embryonic development. Embryos contain relatively few cells and gene activities by individual cells have been determined. Here we review and discuss advances in our understanding of the ascidian embryogenesis emerging from genomic expression studies and analyses at the single cell level.

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

    PubMed

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

    2012-01-01

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

  6. Inferring transcription factor collaborations in gene regulatory networks

    PubMed Central

    2014-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

  8. Function does not follow form in gene regulatory circuits

    PubMed Central

    Payne, Joshua L.; Wagner, Andreas

    2015-01-01

    Gene regulatory circuits are to the cell what arithmetic logic units are to the chip: fundamental components of information processing that map an input onto an output. Gene regulatory circuits come in many different forms, distinct structural configurations that determine who regulates whom. Studies that have focused on the gene expression patterns (functions) of circuits with a given structure (form) have examined just a few structures or gene expression patterns. Here, we use a computational model to exhaustively characterize the gene expression patterns of nearly 17 million three-gene circuits in order to systematically explore the relationship between circuit form and function. Three main conclusions emerge. First, function does not follow form. A circuit of any one structure can have between twelve and nearly thirty thousand distinct gene expression patterns. Second, and conversely, form does not follow function. Most gene expression patterns can be realized by more than one circuit structure. And third, multifunctionality severely constrains circuit form. The number of circuit structures able to drive multiple gene expression patterns decreases rapidly with the number of these patterns. These results indicate that it is generally not possible to infer circuit function from circuit form, or vice versa. PMID:26290154

  9. Effects of nutritional status and gonadal steroids on expression of appetite-regulatory genes in the hypothalamic arcuate nucleus of sheep.

    PubMed

    Archer, Z A; Findlay, P A; McMillen, S R; Rhind, S M; Adam, C L

    2004-09-01

    Sheep exhibit photoperiod-driven seasonal changes in appetite and body weight so that nutritional status increases in long days (LD) and decreases in short days (SD); additionally, they are reproductively active in SD and inactive in LD. We addressed the hypothesis that appetite-regulatory genes in the hypothalamus respond differently to changes in nutritional feedback induced by photoperiod as opposed to food restriction, and that responses would be influenced by gonadal steroid status. Castrated oestradiol-implanted male sheep were kept in SD (8 h light/day) or LD (16 h light/day) for 11 weeks, with ad libitum or restricted food (experiment 1; n=8/group). Rams were kept in SD or LD for 12 weeks with ad libitum or restricted food (experiment 2; n=6/group). Gene expression (by in situ hybridisation) in the hypothalamic arcuate nucleus for leptin receptor (OB-Rb), neuropeptide Y (NPY), pro-opiomelanocortin (POMC) and agouti-related peptide (AGRP) was unaffected by photoperiod treatment, but food restriction increased NPY and AGRP mRNAs, in experiment 1. In experiment 2, mRNAs for POMC and cocaine- and amphetamine-regulated transcript (CART) were up-regulated and AGRP down-regulated in SD, while food restriction increased OB-Rb mRNA, increased NPY and AGRP mRNAs only in LD and decreased POMC mRNA only in SD. Thus, gene expression responded differently to photoperiod and food restriction, and the melanocortin pathway was up-regulated in SD in reproductively activated rams but not in oestradiol-implanted castrates. These data support the hypothesis that hypothalamic appetite-regulatory pathways respond differently to changes in nutritional feedback induced by photoperiod as opposed to food restriction, with gonadal steroid feedback additionally influencing the responses.

  10. Inferring slowly-changing dynamic gene-regulatory networks

    PubMed Central

    2015-01-01

    Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experiments are designed in order to tease out temporal changes in the underlying network. It is typically reasonable to assume that changes in genomic networks are few, because biological systems tend to be stable. We introduce a new model for estimating slow changes in dynamic gene-regulatory networks, which is suitable for high-dimensional data, e.g. time-course microarray data. Our aim is to estimate a dynamically changing genomic network based on temporal activity measurements of the genes in the network. Our method is based on the penalized likelihood with ℓ1-norm, that penalizes conditional dependencies between genes as well as differences between conditional independence elements across time points. We also present a heuristic search strategy to find optimal tuning parameters. We re-write the penalized maximum likelihood problem into a standard convex optimization problem subject to linear equality constraints. We show that our method performs well in simulation studies. Finally, we apply the proposed model to a time-course T-cell dataset. PMID:25917062

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

    PubMed

    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

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

    PubMed Central

    2014-01-01

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

  13. Topological origin of global attractors in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhang, YunJun; Ouyang, Qi; Geng, Zhi

    2015-02-01

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

  14. Framework for engineering finite state machines in gene regulatory networks.

    PubMed

    Oishi, Kevin; Klavins, Eric

    2014-09-19

    Finite state machines are fundamental computing devices at the core of many models of computation. In biology, finite state machines are commonly used as models of development in multicellular organisms. However, it remains unclear to what extent cells can remember state, how they can transition from one state to another reliably, and whether the existing parts available to the synthetic biologist are sufficient to implement specified finite state machines in living cells. Furthermore, how complex multicellular behaviors can be realized by multiple cells coordinating their states with signaling, growth, and division is not well understood. Here, we describe a method by which any finite state machine can be built using nothing more than a suitably engineered network of readily available repressing transcription factors. In particular, we show the mathematical equivalence of finite state machines with a Boolean model of gene regulatory networks. We describe how such networks can be realized with a small class of promoters and transcription factors. To demonstrate the effectiveness of our approach, we show that the behavior of the coarse grained ideal Boolean network model approximates a fine grained delay differential equation model of gene expression. Finally, we explore a framework for the design of more complex systems via an example, synthetic bacterial microcolony edge detection, that illustrates how finite state machines could be used together with cell signaling to construct novel multicellular behaviors.

  15. GeRNet: a gene regulatory network tool.

    PubMed

    Dussaut, J S; Gallo, C A; Cravero, F; Martínez, M J; Carballido, J A; Ponzoni, I

    2017-08-30

    Gene regulatory networks (GRNs) are crucial in every process of life since they govern the majority of the molecular processes. Therefore, the task of assembling these networks is highly important. In particular, the so called model-free approaches have an advantage modeling the complexities of dynamic molecular networks, since most of the gene networks are hard to be mapped with accuracy by any other mathematical model. A highly abstract model-free approach, called rule-based approach, offers several advantages performing data-driven analysis; such as the requirement of the least amount of data. They also have an important ability to perform inferences: its simplicity allows the inference of large size models with a higher speed of analysis. However, regarding these techniques, the reconstruction of the relational structure of the network is partial, hence incomplete, for an effective biological analysis. This situation motivated us to explore the possibility of hybridizing with other approaches, such as biclustering techniques. This led to incorporate a biclustering tool that finds new relations between the nodes of the GRN. In this work we present a new software, called GeRNeT that integrates the algorithms of GRNCOP2 and BiHEA along a set of tools for interactive visualization, statistical analysis and ontological enrichment of the resulting GRNs. In this regard, results associated with Alzheimer disease datasets are presented that show the usefulness of integrating both bioinformatics tools. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    PubMed

    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/ .

  17. Gap Gene Regulatory Dynamics Evolve along a Genotype Network

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2017-10-01

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

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

    PubMed Central

    2013-01-01

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

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

    PubMed Central

    Levine, Herbert; Onuchic, Jose N.

    2017-01-01

    One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression. PMID:28362798

  1. Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation

    PubMed Central

    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

  2. Constraint and Contingency in Multifunctional Gene Regulatory Circuits

    PubMed Central

    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. PMID:23762020

  3. Constraint and contingency in multifunctional gene regulatory circuits.

    PubMed

    Payne, Joshua L; Wagner, Andreas

    2013-01-01

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

  4. Selecting and Weighting Data for Building Consensus Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Steele, Emma; Tucker, Allan

    Microarrays are the major source of data for gene expression activity, allowing the expression of thousands of genes to be measured simultaneously. Gene regulatory networks (GRNs) describe how the expression level of genes affect the expression of the other genes. Modelling GRNs from expression data is a topic of great interest in current bioinformatics research. Previously, we took advantage of publicly available gene expression datasets generated by similar biological studies by drawing together a richer and/or broader collection of data in order to produce GRN models that are more robust, have greater confidence and place less reliance on a single dataset. In this paper a new approach, Weighted Consensus Bayesian Networks, introduces the use of weights in order to place more influence on certain input networks or remove the least reliable networks from the input with encouraging results on both synthetic data and real world yeast microarray datasets.

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

    PubMed

    Koerner, Martha V; Barlow, Denise P

    2010-04-01

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

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

    PubMed

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

    2015-08-01

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

  7. Mapping gene regulatory circuitry of Pax6 during neurogenesis

    PubMed Central

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

    2016-01-01

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

  8. Gene-Transformation-Induced Changes in Chemical Functional Group Features and Molecular Structure Conformation in Alfalfa Plants Co-Expressing Lc-bHLH and C1-MYB Transcriptive Flavanoid Regulatory Genes: Effects of Single-Gene and Two-Gene Insertion.

    PubMed

    Heendeniya, Ravindra G; Yu, Peiqiang

    2017-03-20

    Alfalfa (Medicago sativa L.) genotypes transformed with Lc-bHLH and Lc transcription genes were developed with the intention of stimulating proanthocyanidin synthesis in the aerial parts of the plant. To our knowledge, there are no studies on the effect of single-gene and two-gene transformation on chemical functional groups and molecular structure changes in these plants. The objective of this study was to use advanced molecular spectroscopy with multivariate chemometrics to determine chemical functional group intensity and molecular structure changes in alfalfa plants when co-expressing Lc-bHLH and C1-MYB transcriptive flavanoid regulatory genes in comparison with non-transgenic (NT) and AC Grazeland (ACGL) genotypes. The results showed that compared to NT genotype, the presence of double genes (Lc and C1) increased ratios of both the area and peak height of protein structural Amide I/II and the height ratio of α-helix to β-sheet. In carbohydrate-related spectral analysis, the double gene-transformed alfalfa genotypes exhibited lower peak heights at 1370, 1240, 1153, and 1020 cm(-1) compared to the NT genotype. Furthermore, the effect of double gene transformation on carbohydrate molecular structure was clearly revealed in the principal component analysis of the spectra. In conclusion, single or double transformation of Lc and C1 genes resulted in changing functional groups and molecular structure related to proteins and carbohydrates compared to the NT alfalfa genotype. The current study provided molecular structural information on the transgenic alfalfa plants and provided an insight into the impact of transgenes on protein and carbohydrate properties and their molecular structure's changes.

  9. Gene-Transformation-Induced Changes in Chemical Functional Group Features and Molecular Structure Conformation in Alfalfa Plants Co-Expressing Lc-bHLH and C1-MYB Transcriptive Flavanoid Regulatory Genes: Effects of Single-Gene and Two-Gene Insertion

    PubMed Central

    Heendeniya, Ravindra G.; Yu, Peiqiang

    2017-01-01

    Alfalfa (Medicago sativa L.) genotypes transformed with Lc-bHLH and Lc transcription genes were developed with the intention of stimulating proanthocyanidin synthesis in the aerial parts of the plant. To our knowledge, there are no studies on the effect of single-gene and two-gene transformation on chemical functional groups and molecular structure changes in these plants. The objective of this study was to use advanced molecular spectroscopy with multivariate chemometrics to determine chemical functional group intensity and molecular structure changes in alfalfa plants when co-expressing Lc-bHLH and C1-MYB transcriptive flavanoid regulatory genes in comparison with non-transgenic (NT) and AC Grazeland (ACGL) genotypes. The results showed that compared to NT genotype, the presence of double genes (Lc and C1) increased ratios of both the area and peak height of protein structural Amide I/II and the height ratio of α-helix to β-sheet. In carbohydrate-related spectral analysis, the double gene-transformed alfalfa genotypes exhibited lower peak heights at 1370, 1240, 1153, and 1020 cm−1 compared to the NT genotype. Furthermore, the effect of double gene transformation on carbohydrate molecular structure was clearly revealed in the principal component analysis of the spectra. In conclusion, single or double transformation of Lc and C1 genes resulted in changing functional groups and molecular structure related to proteins and carbohydrates compared to the NT alfalfa genotype. The current study provided molecular structural information on the transgenic alfalfa plants and provided an insight into the impact of transgenes on protein and carbohydrate properties and their molecular structure’s changes. PMID:28335521

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2017-06-12

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

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

    PubMed

    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.

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

    PubMed Central

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

    2017-01-01

    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. PMID:28817344

  14. Modeling stochasticity and robustness in gene regulatory networks

    PubMed Central

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

    2009-01-01

    Motivation: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. Results: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Availability: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/∼garg/genysis.html. Contact: abhishek.garg@epfl.ch PMID:19477975

  15. Modeling stochasticity and robustness in gene regulatory networks.

    PubMed

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

    2009-06-15

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

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

    PubMed

    Deng, Xutao; Geng, Huimin; Ali, Hesham

    2005-08-01

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

  17. Dynamic Gene Regulatory Networks of Human Myeloid Differentiation.

    PubMed

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

    2017-03-27

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

  18. Expression of regulatory nif genes in Rhodobacter capsulatus.

    PubMed Central

    Hübner, P; Willison, J C; Vignais, P M; Bickle, T A

    1991-01-01

    Translational fusions of the Escherichia coli lacZ gene to Rhodobacter capsulatus nif genes were constructed in order to determine the regulatory circuit of nif gene expression in R. capsulatus, a free-living photosynthetic diazotroph. The expression of nifH, nifA (copies I and II), and nifR4 was measured in different regulatory mutant strains under different physiological conditions. The expression of nifH and nifR4 (the analog of ntrA in Klebsiella pneumoniae) depends on the NIFR1/R2 system (the analog of the ntr system in K. pneumoniae), on NIFA, and on NIFR4. The expression of both copies of nifA is regulated by the NIFR1/R2 system and is modulated by the N source of the medium under anaerobic photosynthetic growth conditions. In the presence of ammonia or oxygen, moderate expression of nifA was detectable, whereas nifH and nifR4 were not expressed under these conditions. The implications for the regulatory circuit of nif gene expression in R. capsulatus are discussed and compared with the situation in K. pneumoniae, another free-living diazotroph. PMID:1902215

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

    PubMed

    Kranz, R G; Haselkorn, R

    1985-01-01

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

  20. Efficient computation of minimal perturbation sets in gene regulatory networks

    PubMed Central

    Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; Degueurce, Gwendoline; Ibberson, Mark; Dorier, Julien; Xenarios, Ioannis

    2013-01-01

    In the last few decades, technological and experimental advancements have enabled a more precise understanding of the mode of action of drugs with respect to human cell signaling pathways and have positively influenced the design of new drug compounds. However, as the design of compounds has become increasingly target-specific, the overall effects of a drug on adjacent cellular signaling pathways remain difficult to predict because of the complexity of the interactions involved. Off-target effects of drugs are known to influence their efficacy and safety. Similarly, drugs which are more target-specific also suffer from lack of efficacy because their scope might be too limited in the context of cellular signaling. Even in situations where the signaling pathways targeted by a drug are known, the presence of point mutations in some of the components of the pathways can render a therapy ineffective in a considerable target subpopulation. Some of these issues can be addressed by predicting Minimal Intervention Sets (MIS) of elements of the signaling pathways that when perturbed give rise to a pre-defined cellular phenotype. These minimal gene perturbation sets can then be further used to screen a library of drug compounds in order to discover effective drug therapies. This manuscript describes algorithms that can be used to discover MIS in a gene regulatory network that can lead to a defined cellular phenotype. Algorithms are implemented in our Boolean modeling toolbox, GenYsis. The software binaries of GenYsis are available for download from http://www.vital-it.ch/software/genYsis/. PMID:24391592

  1. A new gene regulatory network model based on BP algorithm for interrogating differentially expressed genes of Sea Urchin.

    PubMed

    Liu, Longlong; Zhao, Tingting; Ma, Meng; Wang, Yan

    2016-01-01

    Computer science and mathematical theories are combined to analyze the complex interactions among genes, which are simplified to a network to establish a theoretical model for the analysis of the structure, module and dynamic properties. In contrast, traditional model of gene regulatory networks often lack an effective method for solving gene expression data because of high durational and spatial complexity. In this paper, we propose a new model for constructing gene regulatory networks using back propagation (BP) neural network based on predictive function and network topology. Combined with complex nonlinear mapping and self-learning, the BP neural network was mapped into a complex network. Network characteristics were obtained from the parameters of the average path length, average clustering coefficient, average degree, modularity, and map's density to simulate the real gene network by an artificial network. Through the statistical analysis and comparison of network parameters of Sea Urchin mRNA microarray data under different temperatures, the value of network parameters was observed. Differentially expressed Sea Urchin genes associated with temperature were determined by calculating the difference in the degree of each gene from different networks. The new model we developed is suitable to simulate gene regulatory network and has capability of determining differentially expressed genes.

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

    PubMed

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

    2015-01-01

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

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

    PubMed

    He, Qinbin; Xia, Zhile; Lin, Bin

    2016-11-07

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

  4. Gene therapy for cancer: regulatory considerations for approval

    PubMed Central

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

    2015-01-01

    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. PMID:26584531

  5. Regulatory sequences of duck hepatitis B virus C gene transcription.

    PubMed Central

    Schneider, R; Will, H

    1991-01-01

    The regulatory elements involved in transcription of the C gene of duck hepatitis B virus (DHBV) were investigated. Several DHBV DNA fragments were assayed for C gene promoter, enhancer, and silencer activity by using a chloramphenicol acetyltransferase (CAT) reporter gene and transfection of established liver and nonliver cell lines. A major transcript initiating at nucleotide positions 2532 and 2533 and three minor transcripts initiating at positions 2453/2454 and 2461 were identified in cells containing these constructs. These positions correspond to the 5' end of the C mRNA and were close to that of the pre-C mRNAs, respectively, found in infected livers. The pre-C mRNAs were only detected when sequences located between the initiation sites of the pre-C and C mRNAs were deleted. These sequences downregulated, in an orientation-independent fashion, a heterologous promoter and were found to contain a consensus motif common to negative transcriptional regulatory elements previously characterized in other cellular and viral genes. C gene promoter activity was only observed in highly differentiated liver cells and was dependent on a short DHBV DNA fragment containing an enhancer core consensus motif. These data indicate that transcription of the DHBV C gene is regulated by positive, negative, and differentiation factor-responsive elements. Images PMID:1920612

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

    PubMed

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

    2015-12-01

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

  7. Beyond antioxidant genes in the ancient NRF2 regulatory network

    PubMed Central

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

    2016-01-01

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

  8. Inference of Gene Regulatory Networks with Sparse Structural Equation Models Exploiting Genetic Perturbations

    PubMed Central

    Cai, Xiaodong; Bazerque, Juan Andrés; Giannakis, Georgios B.

    2013-01-01

    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. PMID:23717196

  9. Establishing neural crest identity: a gene regulatory recipe

    PubMed Central

    Simões-Costa, Marcos; Bronner, Marianne E.

    2015-01-01

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

  10. Statistical ensemble of gene regulatory networks of macrophage differentiation.

    PubMed

    Castiglione, Filippo; Tieri, Paolo; Palma, Alessandro; Jarrah, Abdul Salam

    2016-12-22

    Macrophages cover a major role in the immune system, being the most plastic cell yielding several key immune functions. Here we derived a minimalistic gene regulatory network model for the differentiation of macrophages into the two phenotypes M1 (pro-) and M2 (anti-inflammatory). To test the model, we simulated a large number of such networks as in a statistical ensemble. In other words, to enable the inter-cellular crosstalk required to obtain an immune activation in which the macrophage plays its role, the simulated networks are not taken in isolation but combined with other cellular agents, thus setting up a discrete minimalistic model of the immune system at the microscopic/intracellular (i.e., genetic regulation) and mesoscopic/intercellular scale. We show that within the mesoscopic level description of cellular interaction and cooperation, the gene regulatory logic is coherent and contributes to the overall dynamics of the ensembles that shows, statistically, the expected behaviour.

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

    PubMed

    Gambin, Anna; Lasota, Sławomir; Rutkowski, Michał

    2006-01-01

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

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

    PubMed

    Gambin, Anna; Lasota, Sławomir; Rutkowski, Michał

    2011-01-01

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

  13. Lighting the shadows: methods that expose nuclear and cytoplasmic gene regulatory control.

    PubMed

    Lee, Travis A; Bailey-Serres, Julia

    2017-08-08

    Within cells, myriad interconnected processes orchestrate the progression of gene expression from chromatin, to mRNA, and to protein. Assessment of DNA methylation, histone modification, transcript isoform abundance, and the proteome are frequently performed to examine this progression, but do not resolve many intermediary steps in the coordinated regulation of gene expression. Here, we consider single and multiplexed technologies that yield genome-wide assessment of gene and mRNA activity, from transcription factor access to DNA to de novo synthesis of protein. An emphasis is placed on methods that can resolve gene regulatory processes in cells of defined identity within multicellular organs at spatial and temporal scales, leading to more effective design of gene regulatory cassettes for biotechnology. Copyright © 2017 Elsevier Ltd. All rights reserved.

  14. Transcriptional Targeting in the Airway Using Novel Gene Regulatory Elements

    PubMed Central

    Burnight, Erin R.; Wang, Guoshun; McCray, Paul B.

    2012-01-01

    The delivery of cystic fibrosis transmembrane conductance regulator (CFTR) to airway epithelia is a goal of many gene therapy strategies to treat cystic fibrosis. Because the native regulatory elements of the CFTR are not well characterized, the development of vectors with heterologous promoters of varying strengths and specificity would aid in our selection of optimal reagents for the appropriate expression of the vector-delivered CFTR gene. Here we contrasted the performance of several novel gene-regulatory elements. Based on airway expression analysis, we selected putative regulatory elements from BPIFA1 and WDR65 to investigate. In addition, we selected a human CFTR promoter region (∼ 2 kb upstream of the human CFTR transcription start site) to study. Using feline immunodeficiency virus vectors containing the candidate elements driving firefly luciferase, we transduced murine nasal epithelia in vivo. Luciferase expression persisted for 30 weeks, which was the duration of the experiment. Furthermore, when the nasal epithelium was ablated using the detergent polidocanol, the mice showed a transient loss of luciferase expression that returned 2 weeks after administration, suggesting that our vectors transduced a progenitor cell population. Importantly, the hWDR65 element drove sufficient CFTR expression to correct the anion transport defect in CFTR-null epithelia. These results will guide the development of optimal vectors for sufficient, sustained CFTR expression in airway epithelia. PMID:22447971

  15. Gene regulatory elements of the cardiac conduction system.

    PubMed

    van Duijvenboden, Karel; Ruijter, Jan M; Christoffels, Vincent M

    2014-01-01

    The coordinated contraction of the heart relies on the generation and conduction of the electrical impulse. Aberrations of the function of the cardiac conduction system have been associated with various arrhythmogenic disorders and increased risk of sudden cardiac death. The genetics underlying conduction system function have been investigated using functional studies and genome-wide association studies. Both methods point towards the involvement of ion channel genes and the transcription factors that govern their activity. A large fraction of disease- and trait-associated sequence variants lie within non-coding sequences, enriched with epigenetic marks indicative of regulatory DNA. Although sequence conservation as a result of functional constraint has been a useful property to identify transcriptional enhancers, this identification process has been advanced through the development of techniques such as ChIP-seq and chromatin conformation capture technologies. The role of variation in gene regulatory elements in the cardiac conduction system has recently been demonstrated by studies on enhancers of SCN5A/SCN10A and TBX5. In both studies, a region harbouring a functionally implicated single-nucleotide polymorphism was shown to drive reproducible cardiac expression in a reporter gene assay. Furthermore, the risk variant of the allele abrogated enhancer function in both cases. Functional studies on regulatory DNA will likely receive a boost through recent developments in genome modification technologies.

  16. Phase transitions in the evolution of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Skanata, Antun; Kussell, Edo

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

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

    PubMed

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

    2009-01-01

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

  18. Functional Studies of Regulatory Genes in the Sea Urchin Embryo

    NASA Astrophysics Data System (ADS)

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

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

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

    PubMed

    Yoon, Jinmi; Choi, Heebak; An, Gynheung

    2015-11-01

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

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

    PubMed Central

    Yoon, Jinmi; Choi, Heebak

    2015-01-01

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

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

    PubMed Central

    2010-01-01

    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. PMID:20105328

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

    PubMed

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

    2010-01-27

    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. 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. 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.

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

    PubMed

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

    2004-06-01

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

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

    SciTech Connect

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

    2014-12-24

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

  5. Using shRNA experiments to validate gene regulatory networks.

    PubMed

    Olsen, Catharina; Fleming, Kathleen; Prendergast, Niall; Rubio, Renee; Emmert-Streib, Frank; Bontempi, Gianluca; Quackenbush, John; Haibe-Kains, Benjamin

    2015-06-01

    Quantitative validation of gene regulatory networks (GRNs) inferred from observational expression data is a difficult task usually involving time intensive and costly laboratory experiments. We were able to show that gene knock-down experiments can be used to quantitatively assess the quality of large-scale GRNs via a purely data-driven approach (Olsen et al. 2014). Our new validation framework also enables the statistical comparison of multiple network inference techniques, which was a long-standing challenge in the field. In this Data in Brief we detail the contents and quality controls for the gene expression data (available from NCBI Gene Expression Omnibus repository with accession number GSE53091) associated with our study published in Genomics (Olsen et al. 2014). We also provide R code to access the data and reproduce the analysis presented in this article.

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

    PubMed

    Degl'Innocenti, Andrea; D'Errico, Anna

    2017-01-01

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

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

    PubMed Central

    Degl’Innocenti, Andrea; D’Errico, Anna

    2017-01-01

    The odorant receptor genes, seven transmembrane receptor genes constituting the vastest mammalian gene multifamily, are expressed monogenically and monoallelicaly in each sensory neuron in the olfactory epithelium. This characteristic, often referred to as the one neuron–one receptor rule, is driven by mostly uncharacterized molecular dynamics, generally named odorant receptor gene choice. Much attention has been paid by the scientific community to the identification of sequences regulating the expression of odorant receptor genes within their loci, where related genes are usually arranged in genomic clusters. A number of studies identified transcription factor binding sites on odorant receptor promoter sequences. Similar binding sites were also found on a number of enhancers that regulate in cis their transcription, but have been proposed to form interchromosomal networks. Odorant receptor gene choice seems to occur via the local removal of strongly repressive epigenetic markings, put in place during the maturation of the sensory neuron on each odorant receptor locus. Here we review the fast-changing state of art for the study of regulatory features for odorant receptor genes. PMID:28270833

  8. Gene regulatory mechanisms governing energy metabolism during cardiac hypertrophic growth.

    PubMed

    Lehman, John J; Kelly, Daniel P

    2002-04-01

    Studies in a variety of mammalian species, including humans, have demonstrated a reduction in fatty acid oxidation (FAO) and increased glucose utilization in pathologic cardiac hypertrophy, consistent with reinduction of the fetal energy metabolic program. This review describes results of recent molecular studies aimed at delineating the gene regulatory events which facilitate myocardial energy substrate switches during hypertrophic growth of the heart. Studies aimed at the characterization of transcriptional control mechanisms governing FAO enzyme gene expression in the cardiac myocyte have defined a central role for the fatty acid-activated nuclear receptor peroxisome proliferator-activated receptor alpha (PPAR(alpha)). Cardiac FAO enzyme gene expression was shown to be coordinately downregulated in murine models of ventricular pressure overload, consistent with the energy substrate switch away from fatty acid utilization in the hypertrophied heart. Nuclear protein levels of PPAR(alpha) decline in the ventricle in response to pressure overload, while several Sp and nuclear receptor transcription factors are induced to fetal levels, consistent with their binding to DNA as transcriptional repressors of rate-limiting FAO enzyme genes with hypertrophy. Knowledge of key components of this transcriptional regulatory pathway will allow for the development of genetic engineering strategies in mice that will modulate fatty acid oxidative flux and assist in defining whether energy metabolic derangements play a primary role in the development of pathologic cardiac hypertrophy and eventual progression to heart failure.

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

    PubMed Central

    Cummins, C; Anderson, P

    1988-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

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

    NASA Technical Reports Server (NTRS)

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

    2003-01-01

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

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

    PubMed

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

    2003-11-11

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

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

    PubMed

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

    2015-01-01

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

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

    PubMed Central

    Bollenbach, Tobias; Kishony, Roy

    2011-01-01

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

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

    PubMed

    Laurencot, Carolyn M; Ruppel, Sheryl

    2009-01-01

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

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

    PubMed

    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

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

    PubMed

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

    2007-09-01

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

  19. Signaling and Gene Regulatory Networks in Mammalian Lens Development.

    PubMed

    Cvekl, Ales; Zhang, Xin

    2017-10-01

    Ocular lens development represents an advantageous system in which to study regulatory mechanisms governing cell fate decisions, extracellular signaling, cell and tissue organization, and the underlying gene regulatory networks. Spatiotemporally regulated domains of BMP, FGF, and other signaling molecules in late gastrula-early neurula stage embryos generate the border region between the neural plate and non-neural ectoderm from which multiple cell types, including lens progenitor cells, emerge and undergo initial tissue formation. Extracellular signaling and DNA-binding transcription factors govern lens and optic cup morphogenesis. Pax6, c-Maf, Hsf4, Prox1, Sox1, and a few additional factors regulate the expression of the lens structural proteins, the crystallins. Extensive crosstalk between a diverse array of signaling pathways controls the complexity and order of lens morphogenetic processes and lens transparency. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Autonomous Boolean modelling of developmental gene regulatory networks

    PubMed Central

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

    2013-01-01

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

  1. Optimal finite horizon control in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Liu, Qiuli

    2013-06-01

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

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

    PubMed

    Hu, Zhenhua; Tee, Wee Wei

    2017-03-28

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

  3. Regulatory Fit Effects on Stimulus Identification

    PubMed Central

    Glass, Brian D.; Maddox, W. Todd; Markmana, Arthur B.

    2010-01-01

    This article examines the effects of a fit between a person's global regulatory focus and the local task reward structure on perceptual processing and judgment. On each trial, participants were presented with one of two briefly presented stimuli and were asked to identify it. Participants were placed in a promotion focus (a situationally induced sensitivity to gains) or a prevention focus (a situationally induced sensitivity to losses) and were asked to maximize gains or minimize losses. An asymmetric payoff ratio biased the overall reward toward one identification response over the other. Two experiments tested the role of regulatory fit when internal familiarity and perceptual sensitivity was low or high. When familiarity and sensitivity were low, participants in a regulatory fit (promotion focus with gains or a prevention focus with losses) showed greater perceptual sensitivity, but no response bias differences relative to participants in a regulatory mismatch. When familiarity and sensitivity were high, participants in a regulatory fit showed a response bias toward the high payoff stimulus, but no differences in perceptual sensitivity. Speculation on the neurobiological basis of this effect, as well as implications of this work for clinical disorders, such as depression, is offered. PMID:21264696

  4. Analysis and generic properties of gene regulatory networks with graded response functions

    NASA Astrophysics Data System (ADS)

    Plahte, Erik; Kjøglum, Sissel

    2005-02-01

    The mass of new genomic data has lead to a growing interest in gene regulatory models describing the regulatory aspects of gene activity. In these models, the rates of change of gene product concentrations are expressed as a sum of regulatory switches in terms of sums of products of sigmoid functions, mimicking complex logical on-off functions turning gene activity on and off. The customary way to analyse such equations is to replace the sigmoid functions by step functions and disregard models with autoregulation. This leads to discontinuous equations of motion, but in models without autoregulation, continuous solutions can easily be obtained. With effective autoregulation this simple approach breaks down. As real regulators have finite gain, and autoregulation is ubiquitous in biological systems, we propose a generalised gene regulatory model framework admitting autoregulation and graded sigmoid functions with different steepnesses. Using singular perturbation analysis methods we derive a set of reformulated, continuous equations for the limit solution when the sigmoids approach step functions, and show that the solution for steep sigmoids approaches this limit solution uniformly in a finite time interval. A conspicuous feature of the limit solution is so-called sliding motion during which the solution slides along a threshold hyperplane or the intersection of such hyperplanes. A particular mapping leads to a dual picture of the flow, where the fast parts are magnified at the expense of the slow parts. Combining the two dual pictures, a simple and powerful method to analyse the flow is obtained. We show that for steep sigmoid functions the flow may be highly sensitive to the relative steepnesses of the sigmoids. This has important consequences when stochastic effects are taken into account. Also, it implies that the observation by Glass and Kauffman in 1973 that the qualitative features of the solution do not change provided the underlying “logical” structure

  5. Innovation and robustness in complex regulatory gene networks

    PubMed Central

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

    2007-01-01

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

  6. A Provisional Gene Regulatory Atlas for Mouse Heart Development

    PubMed Central

    Chen, Hailin; VanBuren, Vincent

    2014-01-01

    Congenital Heart Disease (CHD) is one of the most common birth defects. Elucidating the molecular mechanisms underlying normal cardiac development is an important step towards early identification of abnormalities during the developmental program and towards the creation of early intervention strategies. We developed a novel computational strategy for leveraging high-content data sets, including a large selection of microarray data associated with mouse cardiac development, mouse genome sequence, ChIP-seq data of selected mouse transcription factors and Y2H data of mouse protein-protein interactions, to infer the active transcriptional regulatory network of mouse cardiac development. We identified phase-specific expression activity for 765 overlapping gene co-expression modules that were defined for obtained cardiac lineage microarray data. For each co-expression module, we identified the phase of cardiac development where gene expression for that module was higher than other phases. Co-expression modules were found to be consistent with biological pathway knowledge in Wikipathways, and met expectations for enrichment of pathways involved in heart lineage development. Over 359,000 transcription factor-target relationships were inferred by analyzing the promoter sequences within each gene module for overrepresentation against the JASPAR database of Transcription Factor Binding Site (TFBS) motifs. The provisional regulatory network will provide a framework of studying the genetic basis of CHD. PMID:24421884

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

    PubMed

    Liu, Zhi-Ping

    2015-02-01

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

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

    PubMed Central

    Liu, Zhi-Ping

    2015-01-01

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

  9. Developmental Stage, Muscle and Genetic Type Modify Muscle Transcriptome in Pigs: Effects on Gene Expression and Regulatory Factors Involved in Growth and Metabolism

    PubMed Central

    Ayuso, Miriam; Fernández, Almudena; Núñez, Yolanda; Benítez, Rita; Isabel, Beatriz; Fernández, Ana I.; Rey, Ana I.; González-Bulnes, Antonio; Medrano, Juan F.; Cánovas, Ángela; López-Bote, Clemente J.

    2016-01-01

    Iberian pig production includes purebred (IB) and Duroc-crossbred (IBxDU) pigs, which show important differences in growth, fattening and tissue composition. This experiment was conducted to investigate the effects of genetic type and muscle (Longissimus dorsi (LD) vs Biceps femoris (BF)) on gene expression and transcriptional regulation at two developmental stages. Nine IB and 10 IBxDU piglets were slaughtered at birth, and seven IB and 10 IBxDU at four months of age (growing period). Carcass traits and LD intramuscular fat (IMF) content were measured. Muscle transcriptome was analyzed on LD samples with RNA-Seq technology. Carcasses were smaller in IB than in IBxDU neonates (p < 0.001), while growing IB pigs showed greater IMF content (p < 0.05). Gene expression was affected (p < 0.01 and Fold change > 1.5) by the developmental stage (5,812 genes), muscle type (135 genes), and genetic type (261 genes at birth and 113 at growth). Newborns transcriptome reflected a highly proliferative developmental stage, while older pigs showed upregulation of catabolic and muscle functioning processes. Regarding the genetic type effect, IBxDU newborns showed enrichment of gene pathways involved in muscle growth, in agreement with the higher prenatal growth observed in these pigs. However, IB growing pigs showed enrichment of pathways involved in protein deposition and cellular growth, supporting the compensatory gain experienced by IB pigs during this period. Moreover, newborn and growing IB pigs showed more active glucose and lipid metabolism than IBxDU pigs. Moreover, LD muscle seems to have more active muscular and cell growth, while BF points towards lipid metabolism and fat deposition. Several regulators controlling transcriptome changes in both genotypes were identified across muscles and ages (SIM1, PVALB, MEFs, TCF7L2 or FOXO1), being strong candidate genes to drive expression and thus, phenotypic differences between IB and IBxDU pigs. Many of the identified regulators

  10. Developmental Stage, Muscle and Genetic Type Modify Muscle Transcriptome in Pigs: Effects on Gene Expression and Regulatory Factors Involved in Growth and Metabolism.

    PubMed

    Ayuso, Miriam; Fernández, Almudena; Núñez, Yolanda; Benítez, Rita; Isabel, Beatriz; Fernández, Ana I; Rey, Ana I; González-Bulnes, Antonio; Medrano, Juan F; Cánovas, Ángela; López-Bote, Clemente J; Óvilo, Cristina

    2016-01-01

    Iberian pig production includes purebred (IB) and Duroc-crossbred (IBxDU) pigs, which show important differences in growth, fattening and tissue composition. This experiment was conducted to investigate the effects of genetic type and muscle (Longissimus dorsi (LD) vs Biceps femoris (BF)) on gene expression and transcriptional regulation at two developmental stages. Nine IB and 10 IBxDU piglets were slaughtered at birth, and seven IB and 10 IBxDU at four months of age (growing period). Carcass traits and LD intramuscular fat (IMF) content were measured. Muscle transcriptome was analyzed on LD samples with RNA-Seq technology. Carcasses were smaller in IB than in IBxDU neonates (p < 0.001), while growing IB pigs showed greater IMF content (p < 0.05). Gene expression was affected (p < 0.01 and Fold change > 1.5) by the developmental stage (5,812 genes), muscle type (135 genes), and genetic type (261 genes at birth and 113 at growth). Newborns transcriptome reflected a highly proliferative developmental stage, while older pigs showed upregulation of catabolic and muscle functioning processes. Regarding the genetic type effect, IBxDU newborns showed enrichment of gene pathways involved in muscle growth, in agreement with the higher prenatal growth observed in these pigs. However, IB growing pigs showed enrichment of pathways involved in protein deposition and cellular growth, supporting the compensatory gain experienced by IB pigs during this period. Moreover, newborn and growing IB pigs showed more active glucose and lipid metabolism than IBxDU pigs. Moreover, LD muscle seems to have more active muscular and cell growth, while BF points towards lipid metabolism and fat deposition. Several regulators controlling transcriptome changes in both genotypes were identified across muscles and ages (SIM1, PVALB, MEFs, TCF7L2 or FOXO1), being strong candidate genes to drive expression and thus, phenotypic differences between IB and IBxDU pigs. Many of the identified regulators

  11. [Comparative study on the regulatory effects on senescence related cell cycle gene expression by TCM principles of tonifying shen, invigorating pi benefiting qi, and activating blood circulation].

    PubMed

    Chen, Fang-min; Zhao, Wei-kang; Xu, Pin-chu

    2003-11-01

    To compare the effects of TCM therapeutic principles of tonifying Shen (TS), benefiting Qi (BQ), invigorating Pi (IP) and activating blood circulation (ABC) herbs in regulating the gene expression in senescence related cell cycle. Drug sera containing TCM herbs of the above-mentioned principles were used to treat the aged human diploid fibroblast cell line 2BS. The effect of TCM on the senescence related cell cycle and its related gene expression (P16INK4, Cyclin D1 and PCNA) were examined by means of cell proliferative doublings, flow cytometry, RT-PCR and Western blot analysis. TCM herbs of TS and BQ could improve the cell cycle, down-regulate the P16 and Cyclin D1 mRNA/protein expression, up-regulate PCNA mRNA/protein expression, while TCM herbs of IP and ABC showed insignificant effect on these indexes. TCM herbs of TS and BQ have effect in improving cell cycle, it may be achieved through promoting the P16 pathway of gene expression.

  12. Effective carbon partitioning driven by exotic phloem-specific regulatory elements fused to the Arabidopsis thaliana AtSUC2 sucrose-proton symporter gene.

    PubMed

    Srivastava, Avinash C; Ganesan, Savita; Ismail, Ihab O; Ayre, Brian G

    2009-01-20

    AtSUC2 (At1g22710) from Arabidopsis thaliana encodes a phloem-localized sucrose/proton symporter required for efficient photoassimilate transport from source tissues to sink tissues. AtSUC2 plays a key role in coordinating the demands of sink tissues with the output capacity of source leaves, and in maintaining phloem hydrostatic pressure during changes in plant-water balance. Expression and activity are regulated, both positively and negatively, by developmental (sink to source transition) and environmental cues, including light, diurnal changes, photoassimilate levels, turgor pressure, drought and osmotic stress, and hormones. To assess the importance of this regulation to whole-plant growth and carbon partitioning, AtSUC2 cDNA was expressed from two exotic, phloem-specific promoters in a mutant background debilitated for AtSUC2 function. The first was a promoter element from Commelina Yellow Mottle Virus (CoYMV), and the second was the rolC promoter from Agrobacterium rhizogenes. CoYMVp::AtSUC2 cDNA restored growth and carbon partitioning to near wild-type levels, whereas plants harboring rolCp::AtSUC2 cDNA showed only partial complementation. Expressing AtSUC2 cDNA from exotic, phloem-specific promoters argues that strong, phloem-localized expression is sufficient for efficient transport. Expressing AtSUC2 from promoters that foster efficient phloem transport but are subject to regulatory cascades different from the endogenous sucrose/proton symporter genes has implications for biotechnology.

  13. Synergistic effect of ponatinib and epigallocatechin-3-gallate induces apoptosis in chronic myeloid leukemia cells through altering expressions of cell cycle regulatory genes.

    PubMed

    Goker, Bakiye; Caliskan, Cansu; Onur Caglar, Hasan; Kayabasi, Cagla; Balci, Tugce; Erbaykent Tepedelen, Burcu; Aygunes, Duygu; Yilmaz Susluer, Sunde; Mutlu, Zeynep; Selvi Gunel, Nur; Korkmaz, Mehmet; Saydam, Guray; Gunduz, Cumhur; Biray Avci, Cigir

    2014-01-01

    Ponatinib (P) has been used for the treatment of chronic myeloid leukemia (CML) and it is known that inhibition of BCR-ABL fusion protein by ponatinib induces apoptosis of CML cells. Epigallocatechin-3-gallate (EGCG), which is a polyphenol in green tea, induces apoptosis in different types of cancer cells. The purpose of this study was to determine the cytotoxic and apoptotic effects of ponatinib and EGCG combination in K562 CML cell line. This study also aimed to detect alterations of the expression levels of cell cycle-regulation related genes after ponatinib and EGCG combination in K562 CML cell line. The cytotoxic effects of the compounds on K562 cells were determined in a time-and dose-dependent manner by using WST-1 analysis. The combination index (CI) isobologram was used to analyze the data. Apoptotic effects of P-EGCG were defined by flow cytometry and gene expressions were detected by RT-qPCR. IC50values of ponatinib and EGCG were 87.13 nM and 50μM, respectively. CI value of the P-EGCG was 0.658 and the combination showed synergistic effect (ED90 value: 28.39 nM ponatinib, 117.12 μg/ml EGCG). Ponatinib, EGCG and P-EGCG induced apoptosis compared to control cells. CyclinD1 and CDC25A were downregulated by P-EGCG by 2.49 and 2.63-fold, respectively. TGF-β2 was upregulated by 4.57-fold. EGCG possesses cytotoxic and apoptotic properties and may cooperate with the growth inhibiting activity of ponatinib synergistically against CML cells. P-EGCG mediated apoptosis might be associated with upregulation of TGF-β2 gene and downregulation of cyclinD1 and CDC25A genes.

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

    PubMed Central

    2014-01-01

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

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

    PubMed

    Pimanda, John E; Göttgens, Berthold

    2010-01-01

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

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

    PubMed

    Espinosa-Soto, C

    2016-11-01

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

  17. Regulatory dynamics of synthetic gene networks with positive feedback.

    PubMed

    Maeda, Yusuke T; Sano, Masaki

    2006-06-16

    Biological processes are governed by complex networks ranging from gene regulation to signal transduction. Positive feedback is a key element in such networks. The regulation enables cells to adopt multiple internal expression states in response to a single external input signal. However, past works lacked a dynamical aspect of this system. To address the dynamical property of the positive feedback system, we employ synthetic gene circuits in Escherichia coli to measure the rise-time of both the no-feedback system and the positive feedback system. We show that the kinetics of gene expression is slowed down if the gene regulatory system includes positive feedback. We also report that the transition of gene switching behaviors from the hysteretic one to the graded one occurs. A mathematical model based on the chemical reactions shows that the response delay is an inherited property of the positive feedback system. Furthermore, with the aid of the phase diagram, we demonstrate the decline of the feedback activation causes the transition of switching behaviors. Our findings provide a further understanding of a positive feedback system in a living cell from a dynamical point of view.

  18. Using synthetic biology to study gene regulatory evolution.

    PubMed

    Crocker, Justin; Ilsley, Garth R

    2017-09-29

    Transcriptional enhancers specify the precise time, level, and location of gene expression. Disentangling and characterizing the components of enhancer activity in multicellular eukaryotic development has proven challenging because enhancers contain activator and repressor binding sites for multiple factors that each exert nuanced, context-dependent control of enhancer activity. Recent advances in synthetic biology provide an almost unlimited ability to create and modify regulatory elements and networks, offering unprecedented power to study gene regulation. Here we review several studies demonstrating the utility of synthetic biology for studying enhancer function during development and evolution. These studies clearly show that synthetic biology can provide a way to reverse-engineer and reengineer transcriptional regulation in animal genomes with enormous potential for understanding evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed

    Hache, Hendrik; Lehrach, Hans; Herwig, Ralf

    2009-01-01

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

  20. Genomic Aberrations Frequently Alter Chromatin Regulatory Genes in Chordoma

    PubMed Central

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

    2016-01-01

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

  1. Toxin-mediated gene regulatory mechanism in Staphylococcus aureus

    PubMed Central

    Joo, Hwang-Soo; Otto, Michael

    2016-01-01

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

  2. Neurogenic gene regulatory pathways in the sea urchin embryo

    PubMed Central

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

    2016-01-01

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

  3. Gene Regulatory Networks in Cardiac Conduction System Development

    PubMed Central

    Munshi, Nikhil V.

    2014-01-01

    The cardiac conduction system is a specialized tract of myocardial cells responsible for maintaining normal cardiac rhythm. Given its critical role in coordinating cardiac performance, a detailed analysis of the molecular mechanisms underlying conduction system formation should inform our understanding of arrhythmia pathophysiology and affect the development of novel therapeutic strategies. Historically, the ability to distinguish cells of the conduction system from neighboring working myocytes presented a major technical challenge for performing comprehensive mechanistic studies. Early lineage tracing experiments suggested that conduction cells derive from cardiomyocyte precursors, and these claims have been substantiated by using more contemporary approaches. However, regional specialization of conduction cells adds an additional layer of complexity to this system, and it appears that different components of the conduction system utilize unique modes of developmental formation. The identification of numerous transcription factors and their downstream target genes involved in regional differentiation of the conduction system has provided insight into how lineage commitment is achieved. Furthermore, by adopting cutting-edge genetic techniques in combination with sophisticated phenotyping capabilities, investigators have made substantial progress in delineating the regulatory networks that orchestrate conduction system formation and their role in cardiac rhythm and physiology. This review describes the connectivity of these gene regulatory networks in cardiac conduction system development and discusses how they provide a foundation for understanding normal and pathological human cardiac rhythms. PMID:22628576

  4. Evolution of the mammalian embryonic pluripotency gene regulatory network

    PubMed Central

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

    2010-01-01

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

  5. Evolution of the mammalian embryonic pluripotency gene regulatory network.

    PubMed

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

    2010-11-16

    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.

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

    PubMed

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

    2016-01-15

    During embryogenesis the sea urchin early pluteus larva differentiates 40-50 neurons marked by expression of the pan-neural marker synaptotagmin B (SynB) that are distributed along the ciliary band, in the apical plate and pharyngeal endoderm, and 4-6 serotonergic neurons that are confined to the apical plate. Development of all neurons has been shown to depend on the function of Six3. Using a combination of molecular screens and tests of gene function by morpholino-mediated knockdown, we identified SoxC and Brn1/2/4, which function sequentially in the neurogenic regulatory pathway and are also required for the differentiation of all neurons. Misexpression of Brn1/2/4 at low dose caused an increase in the number of serotonin-expressing cells and at higher dose converted most of the embryo to a neurogenic epithelial sphere expressing the Hnf6 ciliary band marker. A third factor, Z167, was shown to work downstream of the Six3 and SoxC core factors and to define a branch specific for the differentiation of serotonergic neurons. These results provide a framework for building a gene regulatory network for neurogenesis in the sea urchin embryo. © 2016. Published by The Company of Biologists Ltd.

  7. CMGRN: a web server for constructing multilevel gene regulatory networks using ChIP-seq and gene expression data.

    PubMed

    Guan, Daogang; Shao, Jiaofang; Deng, Youping; Wang, Panwen; Zhao, Zhongying; Liang, Yan; Wang, Junwen; Yan, Bin

    2014-04-15

    ChIP-seq technology provides an accurate characterization of transcription or epigenetic factors binding on genomic sequences. With integration of such ChIP-based and other high-throughput information, it would be dedicated to dissecting cross-interactions among multilevel regulators, genes and biological functions. Here, we devised an integrative web server CMGRN (constructing multilevel gene regulatory networks), to unravel hierarchical interactive networks at different regulatory levels. The newly developed method used the Bayesian network modeling to infer causal interrelationships among transcription factors or epigenetic modifications by using ChIP-seq data. Moreover, it used Bayesian hierarchical model with Gibbs sampling to incorporate binding signals of these regulators and gene expression profile together for reconstructing gene regulatory networks. The example applications indicate that CMGRN provides an effective web-based framework that is able to integrate heterogeneous high-throughput data and to reveal hierarchical 'regulome' and the associated gene expression programs. http://bioinfo.icts.hkbu.edu.hk/cmgrn; http://www.byanbioinfo.org/cmgrn CONTACT: yanbinai6017@gmail.com or junwen@hku.hk Supplementary Information: Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

    PubMed Central

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

    1987-01-01

    We have sequenced two genes dctB and dctD required for the activation of the C4-dicarboxylate transport structural gene dctA in free-living Rhizobium leguminosarum. The hydropathic profile of the dctB gene product (DctB) suggested that its N-terminal region may be located in the periplasm and its C-terminal region in the cytoplasm. The C-terminal region of DctB was strongly conserved with similar regions of the products of several regulatory genes that may act as environmental sensors, including ntrB, envZ, virA, phoR, cpxA, and phoM. The N-terminal domains of the products of several regulatory genes thought to be transcriptional activators, including ntrC, ompR, virG, phoB and sfrA. In addition, the central and C-terminal regions of DctD were strongly conserved with the products of ntrC and nifA, transcriptional activators that require the alternate sigma factor rpoN (ntrA) as co-activator. The central region of DctD also contained a potential ATP-binding domain. These results are consistent with recent results that show that rpoN product is required for dctA activation, and suggest that DctB plus DctD-mediated transcriptional activation of dctA may be mechanistically similar to NtrB plus NtrC-mediated activation of glnA in E. coli. PMID:3671068

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed

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

    2016-06-01

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

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

    PubMed

    Peter, Isabelle S; Davidson, Eric H

    2016-01-01

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

  13. Effects of Sodium Butyrate Treatment on Histone Modifications and the Expression of Genes Related to Epigenetic Regulatory Mechanisms and Immune Response in European Sea Bass (Dicentrarchus Labrax) Fed a Plant-Based Diet

    PubMed Central

    Díaz, Noelia; Rimoldi, Simona; Ceccotti, Chiara; Gliozheni, Emi; Piferrer, Francesc

    2016-01-01

    Bacteria that inhabit the epithelium of the animals’ digestive tract provide the essential biochemical pathways for fermenting otherwise indigestible dietary fibers, leading to the production of short-chain fatty acids (SCFAs). Of the major SCFAs, butyrate has received particular attention due to its numerous positive effects on the health of the intestinal tract and peripheral tissues. The mechanisms of action of this four-carbon chain organic acid are different; many of these are related to its potent regulatory effect on gene expression since butyrate is a histone deacetylase inhibitor that play a predominant role in the epigenetic regulation of gene expression and cell function. In the present work, we investigated in the European sea bass (Dicentrarchus labrax) the effects of butyrate used as a feed additive on fish epigenetics as well as its regulatory role in mucosal protection and immune homeostasis through impact on gene expression. Seven target genes related to inflammatory response and reinforcement of the epithelial defense barrier [tnfα (tumor necrosis factor alpha) il1β, (interleukin 1beta), il-6, il-8, il-10, and muc2 (mucin 2)] and five target genes related to epigenetic modifications [dicer1(double-stranded RNA-specific endoribonuclease), ehmt2 (euchromatic histone-lysine-N-methyltransferase 2), pcgf2 (polycomb group ring finger 2), hdac11 (histone deacetylase-11), and jarid2a (jumonji)] were analyzed in fish intestine and liver. We also investigated the effect of dietary butyrate supplementation on histone acetylation, by performing an immunoblotting analysis on liver core histone extracts. Results of the eight-week-long feeding trial showed no significant differences in weight gain or SGR (specific growth rate) of sea bass that received 0.2% sodium butyrate supplementation in the diet in comparison to control fish that received a diet without Na-butyrate. Dietary butyrate led to a twofold increase in the acetylation level of histone H4 at

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

    DOE PAGES

    Banf, Michael; Rhee, Seung Y.

    2017-02-01

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

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

    PubMed Central

    Banf, Michael; Rhee, Seung Y.

    2017-01-01

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

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

    PubMed

    Banf, Michael; Rhee, Seung Y

    2017-02-01

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

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

    PubMed

    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.

  18. Effects of bovine fatty acid synthase, stearoyl-coenzyme A desaturase, sterol regulatory element-binding protein 1, and growth hormone gene polymorphisms on fatty acid composition and carcass traits in Japanese Black cattle.

    PubMed

    Matsuhashi, T; Maruyama, S; Uemoto, Y; Kobayashi, N; Mannen, H; Abe, T; Sakaguchi, S; Kobayashi, E

    2011-01-01

    The quality of fat is an important factor in defining the quality of meat. Fat quality is determined by the composition of fatty acids. Among lipid metabolism-related genes, including fatty acid synthesis genes, several genetic variations have been reported in the bovine fatty acid synthase (FASN), stearoyl-CoA desaturase (SCD), sterol regulatory element-binding protein 1 (SREBP1), and GH genes. In the present study, we evaluated the single and epistatic effects of 5 genetic variations (4 SNP and 1 insertion/deletion) in 4 genes (FASN, SCD, SREBP1, and GH) on the fatty acid composition of the longissimus thoracis muscle and carcass and meat quality traits in 480 commercial Japanese Black cattle. Significant single effects of FASN, SCD, and GH(L127V) polymorphisms on the fatty acid composition of the longissimus thoracis muscle were detected. The A293V polymorphism of SCD had the largest effect on myristic acid (C14:0, P < 0.001), myristoleic acid (C14:1, P < 0.001), stearic acid (C18:0, P < 0.001), oleic acid (C18:1, P < 0.001), and MUFA (P < 0.001). Polymorphisms in the FASN, SCD, and SREBP1 genes showed no effect on any meat yield trait. There were no significant epistatic effects on fatty acid composition among pairs of the 3 genes (FASN, SCD, and SREBP1) involved in fatty acid synthesis. No epistatic interactions (P > 0.1) were detected between FASN and SCD for any carcass trait. When the genotypes of 3 markers (FASN, SCD, and GH(L127V)) were substituted from the lesser effect allele to the greater effect allele, the proportion of C18:1 increased by 4.46%. More than 20% of the genetic variance in the C18:1 level could be accounted for by these 3 genetic markers. The present results revealed that polymorphisms in 2 fatty acid synthesis genes (FASN and SCD) independently influenced fatty acid composition in the longissimus thoracis muscle. These results suggest that SNP in the FASN and SCD genes are useful markers for the improvement of fatty acid composition in

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

    DOE PAGES

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

    2014-12-24

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

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

    PubMed Central

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

    2014-01-01

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

  1. Gene regulatory networks and the role of robustness and stochasticity in the control of gene expression

    PubMed Central

    MacNeil, Lesley T.; Walhout, Albertha J.M.

    2011-01-01

    In any given cell, thousands of genes are expressed and work in concert to ensure the cell's function, fitness, and survival. Each gene, in turn, must be expressed at the proper time and in the proper amounts to ensure the appropriate functional outcome. The regulation and expression of some genes are highly robust; their expression is controlled by invariable expression programs. For instance, developmental gene expression is extremely similar in a given cell type from one individual to another. The expression of other genes is more variable: Their levels are noisy and are different from cell to cell and from individual to individual. This can be highly beneficial in physiological responses to outside cues and stresses. Recent advances have enabled the analysis of differential gene expression at a systems level. Gene regulatory networks (GRNs) involving interactions between large numbers of genes and their regulators have been mapped onto graphic diagrams that are used to visualize the regulatory relationships. The further characterization of GRNs has already uncovered global principles of gene regulation. Together with synthetic network biology, such studies are starting to provide insights into the transcriptional mechanisms that cause robust versus stochastic gene expression and their relationships to phenotypic robustness and variability. Here, we discuss GRNs and their topological properties in relation to transcriptional and phenotypic outputs in development and organismal physiology. PMID:21324878

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

    PubMed

    Wang, Canjun; Yi, Ming; Yang, Keli; Yang, Lijian

    2012-01-01

    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. 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 enhanced. Moreover, it

  3. Nitrogen fixation specific regulatory genes of Klebsiella pneumoniae and Rhizobium meliloti share homology with the general nitrogen regulatory gene ntrC of K. pneumoniae.

    PubMed Central

    Buikema, W J; Szeto, W W; Lemley, P V; Orme-Johnson, W H; Ausubel, F M

    1985-01-01

    We have determined the complete nucleotide sequences of three functionally related nitrogen assimilation regulatory genes from Klebsiella pneumoniae and Rhizobium meliloti. These genes are: 1) The K. pneumoniae general nitrogen assimilation regulatory gene ntrC (formerly called glnG), 2) the K. pneumoniae nif-specific regulatory gene nifA, and 3) an R. meliloti nif-specific regulatory gene that appears to be functionally analogous to the K. pneumoniae nifA gene. In addition to the DNA sequence data, gel-purified K. pneumoniae nifA protein was used to determine the amino acid composition of the nifA protein. The K. pneumoniae ntrC and nifA genes code for proteins of 52,259 and 53,319 d respectively. The R. meliloti nifA gene codes for a 59,968 d protein. A central region within each polypeptide, consisting of approximately 200 amino acids, is between 52% and 58% conserved among the three proteins. Neither the amino termini nor the carboxy termini show any conserved sequences. Together with data that shows that the three regulatory proteins activate promoters that share a common consensus sequence in the -10 (5'-TTGCA-3') and -23 (5'-CTGG-3') regions, the sequence data presented here suggest a common evolutionary origin for the three regulatory genes. Images PMID:2989799

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

    PubMed

    Zhang, Qiang; Andersen, Melvin E

    2007-03-02

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

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

    PubMed Central

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

  7. Enhancer Variants Synergistically Drive Dysfunction of a Gene Regulatory Network In Hirschsprung Disease

    DOE PAGES

    Chatterjee, Sumantra; Kapoor, Ashish; Akiyama, Jennifer A.; ...

    2016-09-29

    Common sequence variants in cis-regulatory elements (CREs) are suspected etiological causes of complex disorders. We previously identified an intronic enhancer variant in the RET gene disrupting SOX10 binding and increasing Hirschsprung disease (HSCR) risk 4-fold. We now show that two other functionally independent CRE variants, one binding Gata2 and the other binding Rarb, also reduce Ret expression and increase risk 2- and 1.7-fold. By studying human and mouse fetal gut tissues and cell lines, we demonstrate that reduced RET expression propagates throughout its gene regulatory network, exerting effects on both its positive and negative feedback components. We also provide evidencemore » that the presence of a combination of CRE variants synergistically reduces RET expression and its effects throughout the GRN. These studies show how the effects of functionally independent non-coding variants in a coordinated gene regulatory network amplify their individually small effects, providing a model for complex disorders.« less

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

    Lai, Xin; Wolkenhauer, Olaf; Vera, Julio

    2016-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  11. Identifying sleep regulatory genes using a Drosophila model of insomnia

    PubMed Central

    Seugnet, Laurent; Suzuki, Yasuko; Thimgan, Matthew; Donlea, Jeff; Gimbel, Sarah I.; Gottschalk, Laura; Duntley, Steve P.; Shaw, Paul J.

    2009-01-01

    Although it is widely accepted that sleep must serve an essential biological function, little is known about molecules that underlie sleep regulation. Given that insomnia is a common sleep disorder that disrupts the ability to initiate and maintain restorative sleep, a better understanding of its molecular underpinning may provide crucial insights into sleep regulatory processes. Thus, we created a line of flies using laboratory selection that share traits with human insomnia. After 60 generations insomnia-like (ins-l) flies sleep 60 min a day, exhibit difficulty initiating sleep, difficulty maintaining sleep, and show evidence of daytime cognitive impairment. ins-l flies are also hyperactive and hyper responsive to environmental perturbations. In addition they have difficulty maintaining their balance, have elevated levels of dopamine, are short-lived and show increased levels of triglycerides, cholesterol, and free fatty acids. While their core molecular clock remains intact, ins-l flies lose their ability to sleep when placed into constant darkness. Whole genome profiling identified genes that are modified in ins-l flies. Among those differentially expressed transcripts genes involved in metabolism, neuronal activity, and sensory perception constituted over-represented categories. We demonstrate that two of these genes are upregulated in human subjects following acute sleep deprivation. Together these data indicate that the ins-l flies are a useful tool that can be used to identify molecules important for sleep regulation and may provide insights into both the causes and long-term consequences of insomnia. PMID:19494137

  12. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Santillán Zerón, Moisés

    2007-02-01

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

  13. Genome-wide analysis reveals regulatory role of G4 DNA in gene transcription.

    PubMed

    Du, Zhuo; Zhao, Yiqiang; Li, Ning

    2008-02-01

    G-quadruplex or G4 DNA, a four-stranded DNA structure formed in G-rich sequences, has been hypothesized to be a structural motif involved in gene regulation. In this study, we examined the regulatory role of potential G4 DNA motifs (PG4Ms) located in the putative transcriptional regulatory region (TRR, -500 to +500) of genes across the human genome. We found that PG4Ms in the 500-bp region downstream of the annotated transcription start site (TSS; PG4M(D500)) are associated with gene expression. Generally, PG4M(D500)-positive genes are expressed at higher levels than PG4M(D500)-negative genes, and an increased number of PG4M(D500) provides a cumulative effect. This observation was validated by controlling for attributes, including gene family, function, and promoter similarity. We also observed an asymmetric pattern of PG4M(D500) distribution between strands, whereby the frequency of PG4M(D500) in the coding strand is generally higher than that in the template strand. Further analysis showed that the presence of PG4M(D500) and its strand asymmetry are associated with significant enrichment of RNAP II at the putative TRR. On the basis of these results, we propose a model of G4 DNA-mediated stimulation of transcription with the hypothesis that PG4M(D500) contributes to gene transcription by maintaining the DNA in an open conformation, while the asymmetric distribution of PG4M(D500) considerably reduces the probability of blocking the progression of the RNA polymerase complex on the template strand. Our findings provide a comprehensive view of the regulatory function of G4 DNA in gene transcription.

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

    PubMed

    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.

  15. iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collections

    PubMed Central

    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

    2014-01-01

    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. PMID:25058159

  16. Algebraic model checking for Boolean gene regulatory networks.

    PubMed

    Tran, Quoc-Nam

    2011-01-01

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

  17. Modeling gene regulatory networks: A network simplification algorithm

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  18. ERIC DAVIDSON: STEPS TO A GENE REGULATORY NETWORK FOR DEVELOPMENT

    PubMed Central

    Rothenberg, Ellen V.

    2016-01-01

    Eric Harris Davidson was a unique and creative intellectual force who grappled with the diversity of developmental processes used by animal embryos and wrestled them into an intelligible set of principles, then spent his life translating these process elements into molecularly definable terms through the architecture of gene regulatory networks. He took speculative risks in his theoretical writing but ran a highly organized, rigorous experimental program that yielded an unprecedentedly full characterization of a developing organism. His writings created logical order and a framework for mechanism from the complex phenomena at the heart of advanced multicellular organism development. This is a reminiscence of intellectual currents in his work as observed by the author through the last 30–35 years of Davidson’s life. PMID:26825392

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    1990-01-01

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

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

    PubMed

    Yang, Bin; Liu, Sanrong; Zhang, Wei

    2016-10-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed Central

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

    2013-01-01

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

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

    PubMed Central

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

    2004-01-01

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

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

    PubMed

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

    2011-04-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed

    Shoguchi, Eiichi; Hamaguchi, Makoto; Satoh, Nori

    2008-04-15

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

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

    PubMed Central

    Guzmán-Vargas, Lev; Santillán, Moisés

    2008-01-01

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

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

    PubMed Central

    2011-01-01

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

  12. Evolution of the CNS myelin gene regulatory program.

    PubMed

    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. Copyright © 2015 Elsevier B.V. All rights reserved.

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed Central

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

    2017-01-01

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

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

    USDA-ARS?s Scientific Manuscript database

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

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

    PubMed

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

    2009-08-01

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

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

    PubMed

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

    2015-09-01

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

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

    PubMed Central

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

    1997-01-01

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

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

    PubMed Central

    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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-01-01

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

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

    PubMed

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

    2013-10-01

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

  3. The Impact of Gene Expression Variation on the Robustness and Evolvability of a Developmental Gene Regulatory Network

    PubMed Central

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

    2013-01-01

    Regulatory interactions buffer development against genetic and environmental perturbations, but adaptation requires phenotypes to change. We investigated the relationship between robustness and evolvability within the gene regulatory network underlying development of the larval skeleton in the sea urchin Strongylocentrotus purpuratus. We find extensive variation in gene expression in this network throughout development in a natural population, some of which has a heritable genetic basis. Switch-like regulatory interactions predominate during early development, buffer expression variation, and may promote the accumulation of cryptic genetic variation affecting early stages. Regulatory interactions during later development are typically more sensitive (linear), allowing variation in expression to affect downstream target genes. Variation in skeletal morphology is associated primarily with expression variation of a few, primarily structural, genes at terminal positions within the network. These results indicate that the position and properties of gene interactions within a network can have important evolutionary consequences independent of their immediate regulatory role. PMID:24204211

  4. TDSDMI: Inference of time-delayed gene regulatory network using S-system model with delayed mutual information.

    PubMed

    Yang, Bin; Zhang, Wei; Wang, Haifeng; Song, Chuandong; Chen, Yuehui

    2016-05-01

    Regulatory interactions among target genes and regulatory factors occur instantaneously or with time-delay. In this paper, we propose a novel approach namely TDSDMI based on time-delayed S-system model (TDSS) model and delayed mutual information (DMI) to infer time-delay gene regulatory network (TDGRN). Firstly DMI is proposed to delete redundant regulator factors for each target gene. Secondly restricted gene expression programming (RGEP) is proposed as a new representation of the TDSS model to identify instantaneous and time-delayed interactions. To verify the effectiveness of the proposed method, TDSDMI is applied to both simulated and real biological datasets. Experimental results reveal that TDSDMI performs better than the recent reconstruction methods.

  5. Inferring orthologous gene regulatory networks using interspecies data fusion

    PubMed Central

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

    2015-01-01

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

  6. Stochastic modeling and numerical simulation of gene regulatory networks with protein bursting.

    PubMed

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

    2017-05-21

    Gene expression is inherently stochastic. Advanced single-cell microscopy techniques together with mathematical models for single gene expression led to important insights in elucidating the sources of intrinsic noise in prokaryotic and eukaryotic cells. In addition to the finite size effects due to low copy numbers, translational bursting is a dominant source of stochasticity in cell scenarios involving few short lived mRNA transcripts with high translational efficiency (as is typically the case for prokaryotes), causing protein synthesis to occur in random bursts. In the context of gene regulation cascades, the Chemical Master Equation (CME) governing gene expression has in general no closed form solution, and the accurate stochastic simulation of the dynamics of complex gene regulatory networks is a major computational challenge. The CME associated to a single gene self regulatory motif has been previously approximated by a one dimensional time dependent partial integral differential equation (PIDE). However, to the best of our knowledge, multidimensional versions for such PIDE have not been developed yet. Here we propose a multidimensional PIDE model for regulatory networks involving multiple genes with self and cross regulations (in which genes can be regulated by different transcription factors) derived as the continuous counterpart of a CME with jump process. The model offers a reliable description of systems with translational bursting. In order to provide an efficient numerical solution, we develop a semilagrangian method to discretize the differential part of the PIDE, combined with a composed trapezoidal quadrature formula to approximate the integral term. We apply the model and numerical method to study sustained stochastic oscillations and the development of competence, a particular case of transient differentiation attained by certain bacterial cells under stress conditions. We found that the resulting probability distributions are distinguishable

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

    PubMed

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

    2010-02-04

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

  8. Regulatory elements of Caenorhabditis elegans ribosomal protein genes

    PubMed Central

    2012-01-01

    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 those of all other species

  9. A Trans-Acting Regulatory Gene That Inversely Affects the Expression of the White, Brown and Scarlet Loci in Drosophila

    PubMed Central

    Rabinow, L.; Nguyen-Huynh, A. T.; Birchler, J. A.

    1991-01-01

    A trans-acting regulatory gene, Inr-a, that alters the level of expression of the white eye color locus as an inverse function of the number of its functional copies is described. Several independent lines of evidence demonstrate that this regulatory gene interacts with white via the promoter sequences. Among these are the observations that the inverse regulatory effect is conferred to the Adh gene when fused to the white promoter and that cis-regulatory mutants of white fail to respond. The phenotypic response to Inr-a is found in all tissues in which white is expressed, and mutants of the regulator exhibit a recessive lethality during larval periods. Increased white messenger RNA levels in pupal stages are found in Inr-a/+ individuals versus +/+ and a coordinate response is observed for mRNA levels from the brown and scarlet loci. All are structurally related and participate in pigment deposition. These experiments demonstrate that a single regulatory gene can exert an inverse effect on a target structural locus, a situation postulated from segmental aneuploid studies of gene expression and dosage compensation. PMID:1743487

  10. A review on the computational approaches for gene regulatory network construction.

    PubMed

    Chai, Lian En; Loh, Swee Kuan; Low, Swee Thing; Mohamad, Mohd Saberi; Deris, Safaai; Zakaria, Zalmiyah

    2014-05-01

    Many biological research areas such as drug design require gene regulatory networks to provide clear insight and understanding of the cellular process in living cells. This is because interactions among the genes and their products play an important role in many molecular processes. A gene regulatory network can act as a blueprint for the researchers to observe the relationships among genes. Due to its importance, several computational approaches have been proposed to infer gene regulatory networks from gene expression data. In this review, six inference approaches are discussed: Boolean network, probabilistic Boolean network, ordinary differential equation, neural network, Bayesian network, and dynamic Bayesian network. These approaches are discussed in terms of introduction, methodology and recent applications of these approaches in gene regulatory network construction. These approaches are also compared in the discussion section. Furthermore, the strengths and weaknesses of these computational approaches are described. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. Discovering transcription factor regulatory targets using gene expression and binding data.

    PubMed

    Maienschein-Cline, Mark; Zhou, Jie; White, Kevin P; Sciammas, Roger; Dinner, Aaron R

    2012-01-15

    Identifying the target genes regulated by transcription factors (TFs) is the most basic step in understanding gene regulation. Recent advances in high-throughput sequencing technology, together with chromatin immunoprecipitation (ChIP), enable mapping TF binding sites genome wide, but it is not possible to infer function from binding alone. This is especially true in mammalian systems, where regulation often occurs through long-range enhancers in gene-rich neighborhoods, rather than proximal promoters, preventing straightforward assignment of a binding site to a target gene. We present EMBER (Expectation Maximization of Binding and Expression pRofiles), a method that integrates high-throughput binding data (e.g. ChIP-chip or ChIP-seq) with gene expression data (e.g. DNA microarray) via an unsupervised machine learning algorithm for inferring the gene targets of sets of TF binding sites. Genes selected are those that match overrepresented expression patterns, which can be used to provide information about multiple TF regulatory modes. We apply the method to genome-wide human breast cancer data and demonstrate that EMBER confirms a role for the TFs estrogen receptor alpha, retinoic acid receptors alpha and gamma in breast cancer development, whereas the conventional approach of assigning regulatory targets based on proximity does not. Additionally, we compare several predicted target genes from EMBER to interactions inferred previously, examine combinatorial effects of TFs on gene regulation and illustrate the ability of EMBER to discover multiple modes of regulation. All code used for this work is available at http://dinner-group.uchicago.edu/downloads.html.

  12. Isolation of Sparus auratus prolactin gene and activity of the cis-acting regulatory elements.

    PubMed

    Astola, Antonio; Ortiz, Manuela; Calduch-Giner, Josep A; Pérez-Sánchez, Jaume; Valdivia, Manuel M

    2003-10-15

    A sea bream prolactin (sbPRL) gene was isolated using a prolactin cDNA fragment, generated by PCR as a probe. The gene analyzed comprises 3.5 kb of DNA containing five exons as described previously for other fish PRL genes. Analysis of 1.0 kb of the proximal promoter sequence reveals a consensus TATAA box, up to seven (A/T)3NCAT consensus motifs for binding of the pituitary-specific factor Pit-1 and putative CREB and GATA binding sites. CHO culture cells co-transfected with a sbPRL promoter sequence and a sea bream Pit-1 cDNA expression plasmid showed expression of a linked luciferase reporter gene. Transient expression experiments with 5'-delection mutants reveals at least three regulatory regions on the sbPRL gene, two with a stimulatory effect on transcription and one with apparent inhibitory effect. From a comparative point of view, this study of PRL gene in Sparus auratus, correlates well with those previously published on tilapia and rainbow trout. The molecular data reported will be useful for comparative analysis of gene regulation in the GH/PRL gene family in teleosts.

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

    PubMed

    Strong, Carson

    2011-11-01

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

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

    PubMed

    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.

  15. Ontogeny changes and weaning effects in gene expression patterns of digestive enzymes and regulatory digestive factors in spotted rose snapper (Lutjanus guttatus) larvae.

    PubMed

    Moguel-Hernández, I; Peña, R; Andree, K B; Tovar-Ramirez, D; Bonacic, K; Dumas, S; Gisbert, E

    2016-10-01

    The study of digestive physiology is an important issue in species that have been introduced in aquaculture like the spotted rose snapper (Lutjanus guttatus). The aims of this study were to describe the expression of digestive enzymes (trypsinogen, chymotrypsinogen, α-amylase, lipoprotein lipase, phospholipase A and pepsinogen) and their relation with orexigenic (neuropeptide Y, NPY) and anorexigenic (cholecystokinin, CCK) factors during the larval development and to evaluate the effect of weaning in their expression. The results showed that the transcripts of all the assayed digestive enzymes, with the exception of pepsinogen, and NPY and CCK were already present in L. guttatus from the hatching stage. The expression of all the enzymes was low during the yolk-sac stage (0-2 days after hatching, DAH), whereas after the onset of exogenous feeding at 2 DAH, their expression increased and fluctuated throughout larval development, which followed a similar pattern as in other marine fish species and reflected changes in different types of food items and the progressive maturation of the digestive system. On the other hand, weaning of L. guttatus larvae from live prey onto a microdiet between 25 and 35 DAH significantly affected the relative expression of most pancreatic digestive enzymes during the first weaning days, whereas chymotrypsinogen 2 and lipoprotein lipase remained stable during this period. At the end of co-feeding, larvae showed similar levels of gene expression regardless of the diet (live prey vs. microdiet), which indicated that larvae of L. guttatus were able to adapt their digestive capacities to the microdiet. In contrast, feeding L. guttatus larvae with live feed or microdiet did not affect the expression of CCK and NPY. The relevance of these findings with regard to current larval rearing procedures of L. guttatus is discussed.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

    Li, Xia; Rao, Shaoqi; Jiang, Wei; Li, Chuanxing; Xiao, Yun; Guo, Zheng; Zhang, Qingpu; Wang, Lihong; Du, Lei; Li, Jing; Li, Li; Zhang, Tianwen; Wang, Qing K

    2006-01-01

    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 gene regulations related to

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

    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. Copyright 2009 Elsevier B.V. All rights reserved.

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

    PubMed Central

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

    2016-01-01

    In recent years, it has been reported that the frequency of DNA-methylation regulatory gene mutations – mutations of the genes that regulate gene expression through DNA methylation – is high in acute myeloid leukemia. The objective of the present study was to elucidate the clinical characteristics and prognosis of acute myeloid leukemia with associated DNA-methylation regulatory gene mutation. We studied 308 patients with acute myeloid leukemia. DNA-methylation regulatory gene mutations were observed in 135 of the 308 cases (43.8%). Acute myeloid leukemia associated with a DNA-methylation regulatory gene mutation was more frequent in older patients (P<0.0001) and in patients with intermediate cytogenetic risk (P<0.0001) accompanied by a high white blood cell count (P=0.0032). DNA-methylation regulatory gene mutation was an unfavorable prognostic factor for overall survival in the whole cohort (P=0.0018), in patients aged ≤70 years, in patients with intermediate cytogenetic risk, and in FLT3-ITD-negative patients (P=0.0409). Among the patients with DNA-methylation regulatory gene mutations, 26.7% were found to have two or more such mutations and prognosis worsened with increasing number of mutations. In multivariate analysis DNA-methylation regulatory gene mutation was an independent unfavorable prognostic factor for overall survival (P=0.0424). However, patients with a DNA-methylation regulatory gene mutation who underwent allogeneic stem cell transplantation in first remission had a significantly better prognosis than those who did not undergo such transplantation (P=0.0254). Our study establishes that DNA-methylation regulatory gene mutation is an important unfavorable prognostic factor in acute myeloid leukemia. PMID:27247325

  2. Regulatory and Structural Genes for Lysozymes of Mice

    PubMed Central

    Hammer, Michael F.; Wilson, Allan C.

    1987-01-01

    The molecular and genetic basis of large differences in the concentration of P lysozyme in the small intestine has been investigated by crossing inbred strains of two species of house mouse (genus Mus). The concentration of P in domesticus is about 130-fold higher than in castaneus . An autosomal genetic element determining the concentration of P has been identified and named the P lysozyme regulator, Lzp-r . The level of P in interspecific hybrids (domesticus x castaneus) as well as in certain classes of backcross progeny is intermediate relative to parental levels, which shows that the two alleles of Lzp-r are inherited additively. There are two forms of P lysozyme in the intestine of the interspecific hybrid—one having the heat stability of domesticus P, the other being more stable and presumably the product of the castaneus P locus. These two forms occur in equal amounts, and it appears that Lzp-r acts in trans. The linkage of Lzp-r to three structural genes (Lzp-s, Lzm-s1, and Lzm-s2), one specifying P lysozyme and two specifying M lysozymes, was shown by electrophoretic analysis of backcrosses involving domesticus and castaneus and also domesticus and spretus . The role of regulatory mutations in evolution is discussed in light of these results. PMID:3569879

  3. A Novel Regulatory Gene, Tri10, Controls Trichothecene Toxin Production and Gene Expression

    PubMed Central

    Tag, Andrew G.; Garifullina, Gulnara F.; Peplow, Andrew W.; Ake, Charles; Phillips, T. D.; Hohn, Thomas M.; Beremand, Marian N.

    2001-01-01

    We report here the characterization of Tri10, a novel regulatory gene within the trichothecene gene cluster. Comparison of Tri10 genomic and mRNA sequences revealed that removal of a single 77-bp intron provided a 1,260-bp open reading frame, encoding a 420-amino-acid protein. Disruption of Tri10 in Fusarium sporotrichioides abolished T-2 toxin production and dramatically decreased the transcript accumulation for four trichothecene genes (Tri4, Tri5, Tri6, and Tri101) and an apparent farnesyl pyrophosphate synthetase (Fpps) gene. Conversely, homologous integration of a disruption vector by a single upstream crossover event significantly increased T-2 toxin production and elevated the transcript accumulation of the trichothecene genes and Fpps. Further analysis revealed that disruption of Tri10, and to a greater extent the disruption of Tri6, increased sensitivity to T-2 toxin under certain growth conditions. Although Tri10 is conserved in Fusarium graminearum and Fusarium sambucinum and clearly plays a central role in regulating trichothecene gene expression, it does not show any significant matches to proteins of known or predicted function or to motifs except a single transmembrane domain. We suggest a model in which Tri10 acts upstream of the cluster-encoded transcription factor TRI6 and is necessary for full expression of both the other trichothecene genes and the genes for the primary metabolic pathway that precedes the trichothecene biosynthetic pathway, as well as for wild-type levels of trichothecene self-protection. We further suggest the presence of a regulatory loop where Tri6 is not required for the transcription of Tri10 but is required to limit the expression of Tri10. PMID:11679358

  4. miRNA-Target Gene Regulatory Networks: A Bayesian Integrative Approach to Biomarker Selection with Application to Kidney Cancer

    PubMed Central

    Chekouo, Thierry; Stingo, Francesco C.; Doecke, James D.; Do, Kim-Anh

    2015-01-01

    Summary The availability of cross-platform, large-scale genomic data has enabled the investigation of complex biological relationships for many cancers. Identification of reliable cancer-related biomarkers requires the characterization of multiple interactions across complex genetic networks. MicroRNAs are small non-coding RNAs that regulate gene expression; however, the direct relationship between a microRNA and its target gene is difficult to measure. We propose a novel Bayesian model to identify microRNAs and their target genes that are associated with survival time by incorporating the microRNA regulatory network through prior distributions. We assume that biomarkers involved in regulatory networks are likely associated with survival time. We employ non-local prior distributions and a stochastic search method for the selection of biomarkers associated with the survival outcome. We use KEGG pathway information to incorporate correlated gene effects within regulatory networks. Using simulation studies, we assess the performance of our method, and apply it to experimental data of kidney renal cell carcinoma (KIRC) obtained from The Cancer Genome Atlas. Our novel method validates previously identified cancer biomarkers and identifies biomarkers specific to KIRC progression that were not previously discovered. Using the KIRC data, we confirm that biomarkers involved in regulatory networks are more likely to be associated with survival time, showing connections in one regulatory network for five out of six such genes we identified. PMID:25639276

  5. Massively parallel quantification of the regulatory effects of noncoding genetic variation in a human cohort.

    PubMed

    Vockley, Christopher M; Guo, Cong; Majoros, William H; Nodzenski, Michael; Scholtens, Denise M; Hayes, M Geoffrey; Lowe, William L; Reddy, Timothy E

    2015-08-01

    We report a novel high-throughput method to empirically quantify individual-specific regulatory element activity at the population scale. The approach combines targeted DNA capture with a high-throughput reporter gene expression assay. As demonstration, we measured the activity of more than 100 putative regulatory elements from 95 individuals in a single experiment. In agreement with previous reports, we found that most genetic variants have weak effects on distal regulatory element activity. Because haplotypes are typically maintained within but not between assayed regulatory elements, the approach can be used to identify causal regulatory haplotypes that likely contribute to human phenotypes. Finally, we demonstrate the utility of the method to functionally fine map causal regulatory variants in regions of high linkage disequilibrium identified by expression quantitative trait loci (eQTL) analyses.

  6. Massively parallel quantification of the regulatory effects of noncoding genetic variation in a human cohort

    PubMed Central

    Vockley, Christopher M.; Guo, Cong; Majoros, William H.; Nodzenski, Michael; Scholtens, Denise M.; Hayes, M. Geoffrey; Lowe, William L.; Reddy, Timothy E.

    2015-01-01

    We report a novel high-throughput method to empirically quantify individual-specific regulatory element activity at the population scale. The approach combines targeted DNA capture with a high-throughput reporter gene expression assay. As demonstration, we measured the activity of more than 100 putative regulatory elements from 95 individuals in a single experiment. In agreement with previous reports, we found that most genetic variants have weak effects on distal regulatory element activity. Because haplotypes are typically maintained within but not between assayed regulatory elements, the approach can be used to identify causal regulatory haplotypes that likely contribute to human phenotypes. Finally, we demonstrate the utility of the method to functionally fine map causal regulatory variants in regions of high linkage disequilibrium identified by expression quantitative trait loci (eQTL) analyses. PMID:26084464

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

    PubMed Central

    O'Connor, Timothy R.; Bailey, Timothy L.

    2014-01-01

    Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

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

    PubMed

    O'Connor, Timothy R; Bailey, Timothy L

    2014-01-01

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

  9. Activity-Dependent Human Brain Coding/Noncoding Gene Regulatory Networks

    PubMed Central

    Lipovich, Leonard; Dachet, Fabien; Cai, Juan; Bagla, Shruti; Balan, Karina; Jia, Hui; Loeb, Jeffrey A.

    2012-01-01

    While most gene transcription yields RNA transcripts that code for proteins, a sizable proportion of the genome generates RNA transcripts that do not code for proteins, but may have important regulatory functions. The brain-derived neurotrophic factor (BDNF) gene, a key regulator of neuronal activity, is overlapped by a primate-specific, antisense long noncoding RNA (lncRNA) called BDNFOS. We demonstrate reciprocal patterns of BDNF and BDNFOS transcription in highly active regions of human neocortex removed as a treatment for intractable seizures. A genome-wide analysis of activity-dependent coding and noncoding human transcription using a custom lncRNA microarray identified 1288 differentially expressed lncRNAs, of which 26 had expression profiles that matched activity-dependent coding genes and an additional 8 were adjacent to or overlapping with differentially expressed protein-coding genes. The functions of most of these protein-coding partner genes, such as ARC, include long-term potentiation, synaptic activity, and memory. The nuclear lncRNAs NEAT1, MALAT1, and RPPH1, composing an RNAse P-dependent lncRNA-maturation pathway, were also upregulated. As a means to replicate human neuronal activity, repeated depolarization of SY5Y cells resulted in sustained CREB activation and produced an inverse pattern of BDNF-BDNFOS co-expression that was not achieved with a single depolarization. RNAi-mediated knockdown of BDNFOS in human SY5Y cells increased BDNF expression, suggesting that BDNFOS directly downregulates BDNF. Temporal expression patterns of other lncRNA-messenger RNA pairs validated the effect of chronic neuronal activity on the transcriptome and implied various lncRNA regulatory mechanisms. lncRNAs, some of which are unique to primates, thus appear to have potentially important regulatory roles in activity-dependent human brain plasticity. PMID:22960213

  10. Predicting functional and regulatory divergence of a drug resistance transporter gene in the human malaria parasite.

    PubMed

    Siwo, Geoffrey H; Tan, Asako; Button-Simons, Katrina A; Samarakoon, Upeka; Checkley, Lisa A; Pinapati, Richard S; Ferdig, Michael T

    2015-02-22

    The paradigm of resistance evolution to chemotherapeutic agents is that a key coding mutation in a specific gene drives resistance to a particular drug. In the case of resistance to the anti-malarial drug chloroquine (CQ), a specific mutation in the transporter pfcrt is associated with resistance. Here, we apply a series of analytical steps to gene expression data from our lab and leverage 3 independent datasets to identify pfcrt-interacting genes. Resulting networks provide insights into pfcrt's biological functions and regulation, as well as the divergent phenotypic effects of its allelic variants in different genetic backgrounds. To identify pfcrt-interacting genes, we analyze pfcrt co-expression networks in 2 phenotypic states - CQ-resistant (CQR) and CQ-sensitive (CQS) recombinant progeny clones - using a computational approach that prioritizes gene interactions into functional and regulatory relationships. For both phenotypic states, pfcrt co-expressed gene sets are associated with hemoglobin metabolism, consistent with CQ's expected mode of action. To predict the drivers of co-expression divergence, we integrate topological relationships in the co-expression networks with available high confidence protein-protein interaction data. This analysis identifies 3 transcriptional regulators from the ApiAP2 family and histone acetylation as potential mediators of these divergences. We validate the predicted divergences in DNA mismatch repair and histone acetylation by measuring the effects of small molecule inhibitors in recombinant progeny clones combined with quantitative trait locus (QTL) mapping. This work demonstrates the utility of differential co-expression viewed in a network framework to uncover functional and regulatory divergence in phenotypically distinct parasites. pfcrt-associated co-expression in the CQ resistant progeny highlights CQR-specific gene relationships and possible targeted intervention strategies. The approaches outlined here can be

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

    PubMed Central

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

    2016-01-01

    Motivation microRNAs (miRNAs) play crucial roles in post-transcriptional gene regulation of both plants and mammals, and dysfunctions of miRNAs are often associated with tumorigenesis and development through the effects on their target messenger RNAs (mRNAs). Identifying miRNA functions is critical for understanding cancer mechanisms and determining the efficacy of drugs. Computational methods analyzing high-throughput data offer great assistance in understanding the diverse and complex relationships between miRNAs and mRNAs. However, most of the existing methods do not fully utilise the available knowledge in biology to reduce the uncertainty in the modeling process. Therefore it is desirable to develop a method that can seamlessly integrate existing biological knowledge and high-throughput data into the process of discovering miRNA regulation mechanisms. Results In this article we present an integrative framework, CIDER (Causal miRNA target Discovery with Expression profile and Regulatory knowledge), to predict miRNA targets. CIDER is able to utilise a variety of gene regulation knowledge, including transcriptional and post-transcriptional knowledge, and to exploit gene expression data for the discovery of miRNA-mRNA regulatory relationships. The benefits of our framework is demonstrated by both simulation study and the analysis of the epithelial-to-mesenchymal transition (EMT) and the breast cancer (BRCA) datasets. Our results reveal that even a limited amount of either Transcription Factor (TF)-miRNA or miRNA-mRNA regulatory knowledge improves the performance of miRNA target prediction, and the combination of the two types of knowledge enhances the improvement further. Another useful property of the framework is that its performance increases monotonically with the increase of regulatory knowledge. PMID:27064982

  12. Anomaly detection in gene expression via stochastic models of gene regulatory networks.

    PubMed

    Kim, Haseong; Gelenbe, Erol

    2009-12-03

    The steady-state behaviour of gene regulatory networks (GRNs) can provide crucial evidence for detecting disease-causing genes. However, monitoring the dynamics of GRNs is particularly difficult because biological data only reflects a snapshot of the dynamical behaviour of the living organism. Also most GRN data and methods are used to provide limited structural inferences. In this study, the theory of stochastic GRNs, derived from G-Networks, is applied to GRNs in order to monitor their steady-state behaviours. This approach is applied to a simulation dataset which is generated by using the stochastic gene expression model, and observe that the G-Network properly detects the abnormally expressed genes in the simulation study. In the analysis of real data concerning the cell cycle microarray of budding yeast, our approach finds that the steady-state probability of CLB2 is lower than that of other agents, while most of the genes have similar steady-state probabilities. These results lead to the conclusion that the key regulatory genes of the cell cycle can be expressed in the absence of CLB type cyclines, which was also the conclusion of the original microarray experiment study. G-networks provide an efficient way to monitor steady-state of GRNs. Our method produces more reliable results then the conventional t-test in detecting differentially expressed genes. Also G-networks are successfully applied to the yeast GRNs. This study will be the base of further GRN dynamics studies cooperated with conventional GRN inference algorithms.

  13. Effects of exogenous GABA on gene expression of Caragana intermedia roots under NaCl stress: regulatory roles for H2O2 and ethylene production.

    PubMed

    Shi, Sheng-Qing; Shi, Zheng; Jiang, Ze-Ping; Qi, Li-Wang; Sun, Xiao-Mei; Li, Chun-Xiu; Liu, Jian-Feng; Xiao, Wen-Fa; Zhang, Shou-Gong

    2010-02-01

    gamma-aminobutyric acid (GABA) is a four-carbon non-protein amino acid presented in a wide range of organisms. In this study, a suppression subtractive hybridization (SSH) library was constructed using roots of a legume shrub, Caragana intermedia, with the combined treatment of 300 mm NaCl and 300 mm NaCl + 10 mm GABA. We obtained 224 GABA-regulated unique expressed sequence tags (ESTs) including signal transduction, transcriptional regulation, hormone biosynthesis, reactive oxygen species (ROS) and polyamine metabolism, etc. The key H(2)O(2)-generated genes, NADPH oxidase (CaGR60), peroxidase (CaGR61) and amine oxidase (CaGR62), were regulated at the mRNA level by 10 mm GABA, which clearly inhibited H(2)O(2) accumulation brought about by NaCl stress in roots and leaves with the observation of 3,3'-diaminobenzidine (DAB) staining. Similarly, 10 mm GABA also regulated the expression of 1-aminocyclopropane-1-carboxylic acid (ACC) oxidase (ACO) genes (CaGR30 and CaGR31) and ethylene production in NaCl-treated roots. Surprisingly, these H(2)O(2)-generated genes were enhanced at the mRNA level by a lower concentration of GABA, at 0.25 mm, but not other alternative nitrogen sources, and endogenous GABA accumulated largely just by the application of GABA at either concentration. Our results further proved that GABA, as a signal molecule, participates in regulating the expression of genes in plants under salt stress.

  14. Translating natural genetic variation to gene expression in a computational model of the Drosophila gap gene regulatory network

    PubMed Central

    Kozlov, Konstantin N.; Kulakovskiy, Ivan V.; Zubair, Asif; Marjoram, Paul; Lawrie, David S.; Nuzhdin, Sergey V.; Samsonova, Maria G.

    2017-01-01

    Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on gene expression. We apply a sequence-level model of gap gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect gene expression. The analysis reveals that the sequence variants increase (decrease) gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the gap gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how genetic variation translates to the level of gene regulatory networks via combinatorial SNP effects. PMID:28898266

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

    PubMed

    Yuan, Yinyin; Li, Chang-Tsun; Windram, Oliver

    2011-04-06

    Inferring regulatory relationships among many genes based on their temporal variation in transcript abundance has been a popular research topic. Due to the nature of microarray experiments, classical tools for time series analysis lose power since the number of variables far exceeds the number of the samples. In this paper, we describe some of the existing multivariate inference techniques that are applicable to hundreds of variables and show the potential challenges for small-sample, large-scale data. We propose a directed partial correlation (DPC) method as an efficient and effective solution to regulatory network inference using these data. Specifically for genomic data, the proposed method is designed to deal with large-scale datasets. It combines the efficiency of partial correlation for setting up network topology by testing conditional independence, and the concept of Granger causality to assess topology change with induced interruptions. The idea is that when a transcription factor is induced artificially within a gene network, the disruption of the network by the induction signifies a genes role in transcriptional regulation. The benchmarking results using GeneNetWeaver, the simulator for the DREAM challenges, provide strong evidence of the outstanding performance of the proposed DPC method. When applied to real biological data, the inferred starch metabolism network in Arabidopsis reveals many biologically meaningful network modules worthy of further investigation. These results collectively suggest DPC is a versatile tool for genomics research. The R package DPC is available for download (http://code.google.com/p/dpcnet/).

  16. Transcriptome analysis reveals novel players in the cranial neural crest gene regulatory network

    PubMed Central

    Simões-Costa, Marcos; Tan-Cabugao, Joanne; Antoshechkin, Igor; Sauka-Spengler, Tatjana; Bronner, Marianne E.

    2014-01-01

    The neural crest is an embryonic stem cell population that gives rise to a multitude of derivatives. In particular, the cranial neural crest (CNC) is unique in its ability to contribute to both facial skeleton and peripheral ganglia. To gain further insight into the molecular underpinnings that distinguish the CNC from other embryonic tissues, we have utilized a CNC-specific enhancer as a tool to isolate a pure, region-specific NC subpopulation for transcriptional profiling. The resulting data set reveals previously unknown transcription factors and signaling pathways that may influence the CNC's ability to migrate and/or differentiate into unique derivatives. To elaborate on the CNC gene regulatory network, we evaluated the effects of knocking down known neural plate border genes and early neural crest specifier genes on selected neural crest-enriched transcripts. The results suggest that ETS1 and SOX9 may act as pan-neural crest regulators of the migratory CNC. Taken together, our analysis provides unprecedented characterization of the migratory CNC transcriptome and identifies new links in the gene regulatory network responsible for development of this critical cell population. PMID:24389048

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

    PubMed

    Kim, Haseong; Lee, Jae K; Park, Taesung

    2007-02-01

    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. 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. 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.

  18. Effect of adiponectin on the steroidogenic acute regulatory protein, P450 side chain cleavage enzyme and 3β-hydroxysteroid dehydrogenase gene expression, progesterone and androstenedione production by the porcine uterus during early pregnancy.

    PubMed

    Smolinska, N; Dobrzyn, K; Kiezun, M; Szeszko, K; Maleszka, A; Kaminski, T

    2016-06-01

    Adiponectin and its receptors are expressed in the human and porcine uterus and this endocrine system has important role in the regulation of reproductive processes. The expression of steroidogenic acute regulatory protein (StAR) and 3β-hydroxysteroid dehydrogenase (HSD3B1) were observed in the human and porcine uterus during the oestrous cycle and pregnancy. The de novo synthesis of steroids in the uterus might be a crucial factor for effective implantation and maintenance of pregnancy. We hypothesized that adiponectin modulates the expression of key enzymes in the synthesis of the steroids: StAR, P450 side chain cleavage enzyme (CYP11A1) and HSD3B1, as well as progesterone (P4) and androstenedione (A4) secretion by the porcine uterus. Endometrial and myometrial explants harvested from gilts (n = 5) on days 10 to 11, 12 to 13, 15 to 16 and 27 to 28 of pregnancy and on days 10 to 11 of the oestrous cycle were cultured in vitro in the presence of adiponectin (1, 10 μg/ml), adiponectin with insulin (10 ng/ml) and insulin alone (10 ng/ml). Gene expression was examined by real-time PCR, and the secretion of the steroids was determined by radioimmunoassay. The content of StAR, CYP11A1 and HSD3B1 mRNAs and the secretion of P4 and A4 was modulated by adiponectin in endometrial and myometrial tissue explants during early pregnancy and the oestrous cycle. In this action adiponectin interacted with insulin. Insulin itself also regulated the steroidogenic activity of the porcine uterus. ere we reported, for the first time, the expression of CYP11A1 genes in the porcine endometrium and myometrium. Our novel findings indicate that adiponectin affects basal and insulin-stimulated expression of key steroidogenic genes and production of steroid hormones by the porcine uterus during maternal recognition of pregnancy and implantation.

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

    PubMed

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

    2008-01-15

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

  20. Effects of altered glucose supply and adiposity on expression of hypothalamic energy balance regulatory genes in late gestation growth restricted ovine fetuses.

    PubMed

    Adam, C L; Bake, T; Findlay, P A; Milne, J S; Aitken, R P; Wallace, J M

    2011-11-01

    Intra-uterine growth restriction (IUGR) predisposes obesity in adulthood. This may be due to altered fetal nutrition causing sustained changes within the developing hypothalamic energy balance regulatory system. Using our established ovine model of IUGR, 130-day singleton fetuses (term=147 days) were obtained from growing adolescent mothers on control dietary intake (C), high intake (H) or H with growth hormone administration during either early (H+early GH) or late gestation (H+late GH) (n=6/group). GH increased maternal glycemia for the duration of treatment. H and H+early GH fetuses showed IUGR compared with C fetuses; body weight was partially restored in H+late GH fetuses, with 40% increased adiposity. In the fetal hypothalamic arcuate nucleus (ARC), cocaine- and amphetamine-regulated transcript mRNA (anorexigenic) was decreased in H fetuses and correlated across all groups with total fetal liver glycogen. Neuropeptide Y, agouti-related peptide (orexigenic) and proopiomelanocortin (anorexigenic) mRNAs were not different between groups. Insulin receptor mRNA in the ARC was increased in H, H+early GH and H+late GH fetuses and correlated negatively with fetal plasma insulin. Leptin receptor mRNA in the ARC correlated positively with fetal plasma leptin concentration and fetal fat content. Therefore, in IUGR fetuses, a key anorexigenic neuropeptide is sensitive to altered glucose supply and the hypothalamic leptin-signaling pathway is altered prenatally by increased adiposity and leptinemia. These changes could impact on postnatal energy balance regulation. Copyright © 2011 ISDN. Published by Elsevier Ltd. All rights reserved.

  1. [Effect of gene polymorphism of PPARgamma2 regulatory proteins on the metabolic syndrome in children with nonalcoholic fatty liver disease and obesity].

    PubMed

    2014-04-01

    The aim of this study was to investigate the influence of single nucleotide polymorphism Pro12Ala of PPARγ2 gene in phenotypical manifestations, carbohydrate and lipid metabolism, blood pressure (BP) and tumor necrosis factor alpha (TNF-α) in children with exogenous constitutional obesity (ECO) and nonalcoholic fatty liver disease (NAFLD). 67 children aged from 7 to 17 years were examined; among them 34 patients were diagnosed with NAFLD and 33 children with ECO. The algorithm of examination included assessment of anthropometric parameters, blood lipid profile, glucose indicators and immunoreactive insulin (IRI) on an empty stomach, the calculation of the HOMA-IR index, genetic methods of examination. The study of Pro12Ala polymorphism of PPARγ2 gene showed that patients with NAFLD demonstrated the highest percentage in the frequency of the "wild genotype" Pro/Pro (88,2%) and significantly lower prevalence rate in frequency of allele Ala (11,8%). The presence of the polymorphic allele Ala was associated with lower levels of IRI, HOMA-IR index, a significant reduction of virtually all components of lipid metabolism, systolic blood pressure and pro-inflammatory cytokine TNF-α. Children with genotype X/Ala have greater body weight and higher BMI as compared with homozygous carriers of Pro allele. The detected changes allow us to recommend the use of genetic screening to identify single nucleotide polymorphism Pro12Ala of PPARγ2 gene in obese children in order to determine the degree of risk of metabolic disorders development and implement the preventive measures in a timely manner.

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

    PubMed

    Gazestani, Vahid H; Salavati, Reza

    2015-01-01

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

  3. A yeast one-hybrid and microfluidics-based pipeline to map mammalian gene regulatory networks

    PubMed Central

    Gubelmann, Carine; Waszak, Sebastian M; Isakova, Alina; Holcombe, Wiebke; Hens, Korneel; Iagovitina, Antonina; Feuz, Jean-Daniel; Raghav, Sunil K; Simicevic, Jovan; Deplancke, Bart

    2013-01-01

    The comprehensive mapping of gene promoters and enhancers has significantly improved our understanding of how the mammalian regulatory genome is organized. An important challenge is to elucidate how these regulatory elements contribute to gene expression by identifying their trans-regulatory inputs. Here, we present the generation of a mouse-specific transcription factor (TF) open-reading frame clone library and its implementation in yeast one-hybrid assays to enable large-scale protein–DNA interaction detection with mouse regulatory elements. Once specific interactions are identified, we then use a microfluidics-based method to validate and precisely map them within the respective DNA sequences. Using well-described regulatory elements as well as orphan enhancers, we show that this cross-platform pipeline characterizes known and uncovers many novel TF–DNA interactions. In addition, we provide evidence that several of these novel interactions are relevant in vivo and aid in elucidating the regulatory architecture of enhancers. PMID:23917988

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

    PubMed

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

    2009-01-01

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

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

    PubMed

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

    2016-05-12

    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 the developmental programme is the result of a dynamic driven by a fixed architecture of regulatory interactions, or alternatively, the result of waves of regulatory reorganization is not known. Here we contrast these two alternative models by examining existing expression data derived from the developing human brain in prenatal and postnatal stages. We reveal a sharp change in gene expression profiles at birth across brain areas. This sharp division between foetal and postnatal profiles is not the result of pronounced changes in level of expression of existing gene networks. Instead we demonstrate that the perinatal transition is marked by the widespread regulatory rearrangement within and across existing gene clusters, leading to the emergence of new functional groups. This rearrangement is itself organized into discrete blocks of genes, each targeted by a distinct set of transcriptional regulators and associated to specific biological functions. Our results provide evidence of an acute modular reorganization of the regulatory architecture of the brain transcriptome occurring at birth, reflecting the reassembly of new functional associations required for the normal transition from prenatal to postnatal brain development.

  6. Influence of energy supply on expression of genes encoding for lipogenic enzymes and regulatory proteins in growing beef steers

    USDA-ARS?s Scientific Manuscript database

    Forty crossbred beef steers were used to determine the effects metabolizable energy (ME) intake and of site and complexity of carbohydrate (CHO) infusion on expression of genes encoding lipogenic enzymes and regulatory proteins in subcutaneous (SC), mesenteric (MES) and omental (OM) adipose. Treatm...

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    DOE PAGES

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

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

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

    SciTech Connect

    Yao, Shun; Yoo, Shinjae; Yu, Dantong

    2015-08-28

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

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

    PubMed

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

    2015-10-15

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2016-02-11

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

  14. Detecting regulatory gene-environment interactions with unmeasured environmental factors.

    PubMed

    Fusi, Nicoló; Lippert, Christoph; Borgwardt, Karsten; Lawrence, Neil D; Stegle, Oliver

    2013-06-01

    Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits. In extensive simulation studies, we show that our method is able to accurately reconstruct environmental factors and their interactions with genotype in a variety of settings. We further illustrate the use of our model in a real-world dataset in which one environmental factor has been explicitly experimentally controlled. Our method is able to accurately reconstruct the true underlying environmental factor even if it is not given as an input, allowing to detect genuine genotype-environment interactions. In addition to the known environmental factor, we find unmeasured factors involved in novel genotype-environment interactions. Our results suggest that interactions with both known and unknown environmental factors significantly contribute to gene expression variability. and implementation: Software available at http://pmbio.github.io/envGPLVM/. Supplementary data are available at Bioinformatics online.

  15. Identification of positive and negative transcriptional regulatory elements of the rabbit angiotensin-converting enzyme gene.

    PubMed Central

    Goraya, T Y; Kessler, S P; Kumar, R S; Douglas, J; Sen, G C

    1994-01-01

    The two tissue-specific mRNAs encoding the isozymes of rabbit angiotensin-converting enzyme (ACE) are generated from the same gene by alternative choice of two transcription initiation sites 5.7 kb apart. In the current study, we have characterized the regulatory sites controlling the transcription of the larger pulmonary isozyme mRNA. For this purpose, reporter genes driven by varying lengths of upstream region of the ACE gene were transfected into ACE-producing cells. Our results demonstrated that the transcription of this gene is primarily driven by positive elements within the first 274 bp DNA upstream of the transcription initiation site. The reporter gene driven by this region was expressed in two ACE-producing cells but not in two ACE-non-producing cells thereby establishing its tissue specificity. Our experiments also revealed the existence of a strong negative element located between -692 and -610 positions. This element suppressed the expression of the reporter gene in a dose-dependent and position and orientation-independent fashion thus suggesting that it is a true silencer element. It could also repress the expression of a reporter gene driven by the heterologous strong promoter of the beta-actin gene. The repressing effects of the negative element could be partially overcome by cotransfecting the isolated negative element along with the reporter gene containing the negative element. This result was possibly due to the functional removal of a limiting trans-acting factor which binds to this element. Electrophoretic mobility shift assays revealed that the negative element can form several complexes with proteins present in the nuclear extract of an ACE-producing cell line. At least part of the negative element is strongly conserved in the upstream regions of the human and mouse ACE genes. Images PMID:8165133

  16. Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfural tolerance for ethanologenic yeast

    USDA-ARS?s Scientific Manuscript database

    Composed of linear difference equations, a discrete dynamic system model was designed to reconstruct transcriptional regulations in gene regulatory networks in response to 5-hydroxymethylfurfural, a bioethanol conversion inhibitor for ethanologenic yeast Saccharomyces cerevisiae. The modeling aims ...

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

    SciTech Connect

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

    2005-01-05

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

  18. Molecular analysis of the transcriptional regulatory region of an early baculovirus gene.

    PubMed Central

    Nissen, M S; Friesen, P D

    1989-01-01

    Transcription of the gene encoding a 35,000-molecular-weight protein (35K protein) from the EcoRI-S region (86.8 to 87.8 map units) of Autographa california nuclear polyhedrosis virus (AcMNPV) occurs early in infection and declines later. The region promoting the gene for the 35K protein, extending from 426 base pairs (bp) upstream to 12 bp downstream from the RNA start site, was linked to the bacterial chloramphenicol acetyltransferase gene (CAT) for analysis. CAT expression was monitored in cells that were transfected with plasmids containing the promoter-CAT fusion as well as cells infected with recombinant viruses containing the chimeric gene inserted into the AcMNPV genome. Mapping of the 5' ends of CAT-specific RNAs indicated that transcription initiated from the proper sites in both assays; moreover, the promoter fragment retained its early activity, despite an alternate location in the viral genome. The 5' boundary of upstream regulatory sequences was determined by constructing deletions of the promoter fragment extending toward the early RNA start site (position +1). In transient assays, a gradual reduction in CAT expression occurred as sequences from positions -426 to -31 were removed. In contrast, promoter deletions from positions -426 to -155 in recombinant viruses exhibited no effect on CAT expression, whereas deletions to position -55 abolished early expression but had no effect on late expression. Late CAT expression was eliminated when deletions to position -4 removed part of the late RNA start site. DNA signals potentiating early transcription were therefore located upstream (between positions -155 and -55) from those involved in late transcription of the gene encoding the 35K protein. Potential consensus sequences for early and late regulatory elements were identified. Images PMID:2642976

  19. Regulatory effects of fisetin on microglial activation.

    PubMed

    Chuang, Jing-Yuan; Chang, Pei-Chun; Shen, Yi-Chun; Lin, Chingju; Tsai, Cheng-Fang; Chen, Jia-Hong; Yeh, Wei-Lan; Wu, Ling-Hsuan; Lin, Hsiao-Yun; Liu, Yu-Shu; Lu, Dah-Yuu

    2014-06-26

    Increasing evidence suggests that inflammatory processes in the central nervous system that are mediated by microglial activation play a key role in neurodegeneration. Fisetin, a plant flavonol commonly found in fruits and vegetables, is frequently added to nutritional supplements due to its antioxidant properties. In the present study, treatment with fisetin inhibited microglial cell migration and ROS (reactive oxygen species) production. Treatment with fisetin also effectively inhibited LPS plus IFN-γ-induced nitric oxide (NO) production, and inducible nitric oxide synthase (iNOS) expression in microglial cells. Furthermore, fisetin also reduced expressions of iNOS and NO by stimulation of peptidoglycan, the major component of the Gram-positive bacterium cell wall. Fisetin also inhibited the enhancement of LPS/IFN-γ- or peptidoglycan-induced inflammatory mediator IL (interlukin)-1 β expression. Besides the antioxidative and anti-inflammatory effects of fisetin, our study also elucidates the manner in fisetin-induced an endogenous anti-oxidative enzyme HO (heme oxygenase)-1 expression. Moreover, the regulatory molecular mechanism of fisetin-induced HO-1 expression operates through the PI-3 kinase/AKT and p38 signaling pathways in microglia. Notably, fisetin also significantly attenuated inflammation-related microglial activation and coordination deficit in mice in vivo. These findings suggest that fisetin may be a candidate agent for the development of therapies for inflammation-related neurodegenerative diseases.

  20. Gene regulatory networks that control the specification of neural-crest cells in the lamprey.

    PubMed

    Nikitina, Natalya V; Bronner-Fraser, Marianne

    2009-04-01

    The lamprey is the only basal vertebrate in which large-scale gene perturbation analyses are feasible at present. Studies on this unique animal model promise to contribute both to the understanding of the basic neural-crest gene regulatory network architecture, and evolution of the neural crest. In this review, we summarize the currently known regulatory relationships underlying formation of the vertebrate neural crest, and discuss new ways of addressing the many remaining questions using lamprey as an experimental model.

  1. Identification and characterization of promoters and cis-regulatory elements of genes involved in secondary metabolites production in hop (Humulus lupulus. L).

    PubMed

    Duraisamy, Ganesh Selvaraj; Mishra, Ajay Kumar; Kocabek, Tomas; Matoušek, Jaroslav

    2016-10-01

    Molecular and biochemical studies have shown that gene contains single or combination of different cis-acting regulatory elements are actively controlling the transcriptional regulation of associated genes, downstream effects of these result in the modulation of various biological pathways such as biotic/abiotic stress responses, hormonal responses to growth and development processes and secondary metabolite production. Therefore, the identification of promoters and their cis-regulatory elements is one of intriguing area to study the dynamic complex regulatory network of genes activities by integrating computational, comparative, structural and functional genomics. Several bioinformatics servers or database have been established to predict the cis-acting elements present in the promoter region of target gene and their association with the expression profiles in the TFs. The aim of this study is to predict possible cis-acting regulatory elements that have putative role in the transcriptional regulation of a dynamic network of metabolite gene activities controlling prenylflavonoid and bitter acids biosynthesis in hop (Humulus lupulus). Recent release of hop draft genome enabled us to predict the possible cis-acting regulatory elements by extracting 2kbp of 5' regulatory regions of genes important for lupulin metabolome biosynthesis, using Plant CARE, PLACE and Genomatix Matinspector professional databases. The result reveals the plausible role of cis-acting regulatory elements in the regulation of gene expression primarily involved in lupulin metabolome biosynthesis including under various stress conditions.

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

    PubMed

    Gao, Feng; Davidson, Eric H

    2008-04-22

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

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

    PubMed

    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.

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

    PubMed

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

    2012-01-01

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

  5. Identification of a novel miRNA-target gene regulatory network in osteosarcoma by integrating transcriptome analysis

    PubMed Central

    He, Chunlei; Gao, Hui; Fan, Xiaona; Wang, Maoyuan; Liu, Wuyang; Huang, Weiming; Yang, Yadong

    2015-01-01

    Osteosarcoma remains a leading cause of cancer death in children and young adolescents. Although the introduction of multiagent chemotherapy, survival rates have not improved in two decades. Therefore, it is urgently needed to know the details regarding molecular etiology to driving therapeutic inroads for this disease. In this study we performed an integrated analysis of miRNA and mRNA expression data to explore the dysregulation of miRNA and miRNA-target gene regulatory network underlying OS. 59 differentially expressed miRNAs were identified, with 28 up-regulated and 31 down-regulated miRNAs by integrating OS miRNA expression data sets available. Using miRWalk databases prediction, we performed an anticorrelated analysis of miRNA and genes expression identified by a integrated analysis of gene expression data to identify 109 differently expressed miRNA target genes. A novel miRNA-target gene regulatory network was constructed with the miRNA-target gene pairs. miR-19b-3p, miR-20a-5p, miR-124-3p and their common target CCND2, the nodal points of regulatory network, may play important roles in OS. Bioinformatics analysis of biological functions and pathways demonstrated that target genes of miRNAs are highly correlated with carcinogenesis. Our findings may help to understand the molecular mechanisms of OS and identify targets of effective targeted therapies for OS. PMID:26339404

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

    PubMed

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

    2017-08-07

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

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

    PubMed

    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.

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

    DOE PAGES

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

    2016-03-18

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

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

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

    SciTech Connect

    Wang, Xuting; Tomso, Daniel J.; Liu Xuemei; Bell, Douglas A. . E-mail: BELL1@niehs.nih.gov

    2005-09-01

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

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

    PubMed

    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.

  13. Design of a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations

    PubMed Central

    Spirov, Alexander V.; Holloway, David M.

    2010-01-01

    A new approach to design a dynamic model of genes with multiple autonomous regulatory modules by evolutionary computations is proposed. The approach is based on Genetic Algorithms (GA), with new crossover operators especially designed for these purposes. The new operators use local homology between parental strings to preserve building blocks found by the algorithm. The approach exploits the subbasin-portal architecture of the fitness functions suitable for this kind of evolutionary modeling. This architecture is significant for Royal Road class fitness functions. Two real-life Systems Biology problems with such fitness functions are implemented here: evolution of the bacterial promoter rrnPl and of the enhancer of the Drosophila even-skipped gene. The effectiveness of the approach compared to standard GA is demonstrated on several benchmark and real-life tasks. PMID:20930945

  14. Luteal expression of cytochrome P450 side-chain cleavage, steroidogenic acute regulatory protein, 3beta-hydroxysteroid dehydrogenase, and 20alpha-hydroxysteroid dehydrogenase genes in late pregnant rats: effect of luteinizing hormone and RU486.

    PubMed

    Stocco, C O; Chedrese, J; Deis, R P

    2001-10-01

    A decrease in serum progesterone at the end of pregnancy is essential for the induction of parturition in rats. We have previously demonstrated that LH participates in this process through: 1) inhibiting 3beta-hydroxysteroid dehydrogenase (3beta-HSD) activity and 2) stimulating progesterone catabolism by inducing 20alpha-hydroxysteroid dehydrogenase (20alpha-HSD) activity. The objective of this investigation was to determine the effect of LH and progesterone on the luteal expression of the steroidogenic acute regulatory protein (StAR), cytochrome P450 side-chain cleavage (P450(scc)), 3beta-HSD, and 20alpha-HSD genes. Gene expression was analyzed by Northern blot analysis 24 and 48 h after administration of LH or vehicle on Day 19 of pregnancy. StAR and 3beta-HSD mRNA levels were lower in LH-treated rats than in rats administered with vehicle at both time points studied. P450(scc) mRNA levels were unaffected by LH. The 20alpha-HSD mRNA levels were not different between LH and control rats 24 h after treatment; however, greater expression of 20alpha-HSD, with respect to controls, was observed in LH-treated rats 48 h after treatment. Luteal progesterone content dropped in LH-treated rats at both time points studied, whereas serum progesterone decreased after 48 h only. In a second set of experiments, the anti-progesterone RU486 was injected intrabursally on Day 20 of pregnancy. RU486 had no effect on 3beta-HSD or P450(scc) expression but increased 20alpha-HSD mRNA levels after 8 h treatment. In conclusion, the luteolytic effect of LH is mediated by a drop in StAR and 3beta-HSD expression without effect on P450(scc) expression. We also provide the first in vivo evidence indicating that a decrease in luteal progesterone content may be an essential step toward the induction of 20alpha-HSD expression at the end of pregnancy in rats.

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

    PubMed Central

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

    1993-01-01

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

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

    PubMed Central

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

    2010-01-01

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

  17. Effect of Annexin A1 gene on the proliferation and invasion of esophageal squamous cell carcinoma cells and its regulatory mechanisms.

    PubMed

    Han, Gaohua; Lu, Kaijin; Huang, Junxing; Ye, Jun; Dai, Shengbin; Ye, Yunyao; Zhang, Lixin

    2017-02-01

    The aim of this study was to examine the effect of Annexin A1 (ANXA1) on the proliferation, migration and invasion of esophageal squamous cell carcinoma (ESCC) cells and its possible mechanisms of action. After constructing the ANXA1 overexpression plasmid, we transfected this plasmid and/or microRNA (miRNA)‑196a mimic into ESCC cells (Eca109 cell line). Methyl thiazolyl tetrazolium (MTT) assay and Transwell chamber assay were performed to determine cell proliferation, migration and invasion, respectively. Western blot analysis was used to examine the protein expression levels of ANXA1, Snail and E-cadherin. RT-PCR was used to detect the expression of miRNA-196a. Our results revealed that ANXA1 expression was upregulated in the cells transfected with the ANXA1 overexpression plasmid, and cell proliferation, migration and invasion were significantly increased (p=0.004, p<0.001 and p=0.011, respectively). In the cells transfected with the miRNA‑196a mimic, miRNA‑196a expression was significantly upregulated (p<0.001). However, miRNA-196a expression was downregulated in the cells transfected with the ANXA1 overexpression plasmid. In addition, in the cells transfected with the miRNA‑196a mimic, cell proliferation, migration and invasion were significantly decreased (p=0.027, p=0.009 and p=0.021, respectively). In the cells transfected with the ANXA1 overexpression plasmid, the expression of Snail was upregulated and that of E-cadherin was downregulated. However, the opposite was observed in the cells transfected with the miRNA‑196a mimic. Our findings thus demonstrate that ANXA1 promotes the proliferation of Eca109 cells, and increases the expression of Snail, whereas it inhibits that of E-cadherin, thus enhancing the migration and invasion of ESCC cells. miRNA-196a negatively regulates the expression of ANXA1, thereby inhibiting the proliferation, invasion and metastasis of ESCC cells.

  18. Effect of Annexin A1 gene on the proliferation and invasion of esophageal squamous cell carcinoma cells and its regulatory mechanisms

    PubMed Central

    Han, Gaohua; Lu, Kaijin; Huang, Junxing; Ye, Jun; Dai, Shengbin; Ye, Yunyao; Zhang, Lixin

    2017-01-01

    The aim of this study was to examine the effect of Annexin A1 (ANXA1) on the proliferation, migration and invasion of esophageal squamous cell carcinoma (ESCC) cells and its possible mechanisms of action. After constructing the ANXA1 overexpression plasmid, we transfected this plasmid and/or microRNA (miRNA)-196a mimic into ESCC cells (Eca109 cell line). Methyl thiazolyl tetrazolium (MTT) assay and Transwell chamber assay were performed to determine cell proliferation, migration and invasion, respectively. Western blot analysis was used to examine the protein expression levels of ANXA1, Snail and E-cadherin. RT-PCR was used to detect the expression of miRNA-196a. Our results revealed that ANXA1 expression was upregulated in the cells transfected with the ANXA1 overexpression plasmid, and cell proliferation, migration and invasion were significantly increased (p=0.004, p<0.001 and p=0.011, respectively). In the cells transfected with the miRNA-196a mimic, miRNA-196a expression was significantly upregulated (p<0.001). However, miRNA-196a expression was downregulated in the cells transfected with the ANXA1 overexpression plasmid. In addition, in the cells transfected with the miRNA-196a mimic, cell proliferation, migration and invasion were significantly decreased (p=0.027, p=0.009 and p=0.021, respectively). In the cells transfected with the ANXA1 overexpression plasmid, the expression of Snail was upregulated and that of E-cadherin was downregulated. However, the opposite was observed in the cells transfected with the miRNA-196a mimic. Our findings thus demonstrate that ANXA1 promotes the proliferation of Eca109 cells, and increases the expression of Snail, whereas it inhibits that of E-cadherin, thus enhancing the migration and invasion of ESCC cells. miRNA-196a negatively regulates the expression of ANXA1, thereby inhibiting the proliferation, invasion and metastasis of ESCC cells. PMID:28035369

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

    PubMed

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

    2012-08-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2013-07-01

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

  2. Inference of gene regulatory networks using S-system: a unified approach.

    PubMed

    Wang, H; Qian, L; Dougherty, E

    2010-03-01

    With the increased availability of DNA microarray time-series data, it is possible to discover dynamic gene regulatory networks (GRNs). S-system is a promising model to capture the rich dynamics of GRNs. However, owing to the complexity of the inference problem and limited number of available data comparing to the number of unknown kinetic parameters, S-system can only be applied to a very small GRN with few parameters. This significantly limits its applications. A unified approach to infer GRNs using the S-system model is proposed. In order to discover the structure of large-scale GRNs, a simplified S-system model is proposed that enables fast parameter estimation to determine the major gene interactions. If a detailed S-system model is desirable for a subset of genes, a two-step method is proposed where the range of the parameters will be determined first using genetic programming and recursive least square estimation. Then the mean values of the parameters will be estimated using a multi-dimensional optimisation algorithm. Both the downhill simplex algorithm and modified Powell algorithm are tested for multi-dimensional optimisation. A 50-dimensional synthetic model with 51 parameters for each gene is tested for the applicability of the simplified S-system model. In addition, real measurement data pertaining to yeast protein synthesis are used to demonstrate the effectiveness of the proposed two-step method to identify the detailed interactions among genes in small GRNs.

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

    PubMed Central

    Chaouiya, Claudine; Ourrad, Ouerdia; Lima, Ricardo

    2013-01-01

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

  4. EGRINs (Environmental Gene Regulatory Influence Networks) in Rice That Function in the Response to Water Deficit, High Temperature, and Agricultural Environments[OPEN

    PubMed Central

    Hafemeister, Christoph; Nicotra, Adrienne B.; Jagadish, S.V. Krishna; Bonneau, Richard; Purugganan, Michael

    2016-01-01

    Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosome-free regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference. PMID:27655842

  5. Mapping Association between Long-Range Cis-Regulatory Regions and Their Target Genes Using Comparative Genomics

    NASA Astrophysics Data System (ADS)

    Mongin, Emmanuel; Dewar, Ken; Blanchette, Mathieu

    In chordates, long-range cis-regulatory regions are involved in the control of transcription initiation (either as repressors or enhancers). They can be located as far as 1 Mb from the transcription start site of the target gene and can regulate more than one gene. Therefore, proper characterization of functional interactions between long-range cis-regulatory regions and their target genes remains problematic. We present a novel method to predict such interactions based on the analysis of rearrangements between the human and 16 other vertebrate genomes. Our method is based on the assumption that genome rearrangements that would disrupt the functional interaction between a cis-regulatory region and its target gene are likely to be deleterious. Therefore, conservation of synteny through evolution would be an indication of a functional interaction. We use our algorithm to classify a set of 1,406,084 putative associations from the human genome. This genome-wide map of interactions has many potential applications, including the selection of candidate regions prior to in vivo experimental characterization, a better characterization of regulatory regions involved in position effect diseases, and an improved understanding of the mechanisms and importance of long-range regulation.

  6. Identification of genes involved in regulatory mechanism of pigments in broiler chickens.

    PubMed

    Tarique, T M; Yang, S; Mohsina, Z; Qiu, J; Yan, Z; Chen, G; Chen, A

    2014-09-05

    Chicken is an important model organism that unites the evolutionary gap between mammals and other vertebrates and provide major source of protein from meat and eggs for all over the world population. However, specific genes underlying the regulatory mechanism of broiler pigmentation have not yet been determined. In order to better understand the genes involved in the mechanism of pigmentation in the muscle tissues of broilers, the Affymetrix microarray hybridization experiment platform was used to identify gene expression profiles at 7 weeks of age. Broilers fed canthaxanthin, natural lutein, and orangeII pigments (100 mg/kg) were used to explore gene expression profiles). Our data showed that the 7th week of age was a very important phase with regard to gene expression profiles. We identified a number of differentially expressed genes; in canthaxanthin, natural lutein, and orangeII, there were 54 (32 upregulated and 22 downregulated), 23 (15 upregulated and 8 downregulated), and 7 (5 upregulated and 2 downregulated) known genes, respectively. Our data indicate that the numbers of differentially expressed genes were more upregulated than downregulated, and several genes showed conserved signaling to previously known functions. Thus, functional characterization of differentially expressed genes revealed several categories that are involved in important biological processes, including pigmentation, growth, molecular mechanisms, fat metabolism, cell proliferation, immune response, lipid metabolism, and protein synthesis and degradation. The results of the present study demonstrate that the genes associated with canthaxanthin, natural lutein, and orangeII are key regulatory genes that control the regulatory mechanisms of pigmentation.

  7. Time lagged information theoretic approaches to the reverse engineering of gene regulatory networks

    PubMed Central

    2010-01-01

    Background A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of time-series microarray expression data in terms of the number of time-points. In this paper, we study this problem by analyzing the behaviour of three algorithms based on information theory and dynamic Bayesian network (DBN) models. These algorithms were implemented on different sizes of data generated by synthetic networks. Experiments show that the inference accuracy of these algorithms reaches a saturation point after a specific data size brought about by a saturation in the pair-wise mutual information (MI) metric; hence there is a theoretical limit on the inference accuracy of information theory based schemes that depends on the number of time points of micro-array data used to infer GRNs. This illustrates the fact that MI might not be the best metric to use for GRN inference algorithms. To circumvent the limitations of the MI metric, we introduce a new method of computing time lags between any pair of genes and present the pair-wise time lagged Mutual Information (TLMI) and time lagged Conditional Mutual Information (TLCMI) metrics. Next we use these new metrics to propose novel GRN inference schemes which provides higher inference accuracy based on the precision and recall parameters. Results It was observed that beyond a certain number of time-points (i.e., a specific size) of micro-array data, the performance of the algorithms measured in terms of the recall-to-precision ratio saturated due to the saturation in the calculated pair-wise MI metric with increasing data size. The proposed algorithms were compared to existing approaches on four different biological networks. The resulting networks were evaluated based on the benchmark precision and recall metrics and the results favour our approach. Conclusions To alleviate the effects of data size on information theory based GRN

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

    PubMed

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

    2011-10-01

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

  9. DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

    PubMed Central

    Gerstein, Mark

    2016-01-01

    Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with

  10. DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

    PubMed

    Wang, Daifeng; He, Fei; Maslov, Sergei; Gerstein, Mark

    2016-10-01

    Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal) and another subsystem's (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily

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

    PubMed Central

    2013-01-01

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

  12. Regulatory logic of pan-neuronal gene expression in C. elegans

    PubMed Central

    Stefanakis, Nikolaos; Carrera, Ines; Hobert, Oliver

    2015-01-01

    While neuronal cell types display an astounding degree of phenotypic diversity, most if not all neuron types share a core panel of terminal features. However, little is known about how pan-neuronal expression patterns are genetically programmed. Through an extensive analysis of the cis-regulatory control regions of a battery of pan-neuronal C.elegans genes, including genes involved in synaptic vesicle biology and neuropeptide signaling, we define a common organizational principle in the regulation of pan-neuronal genes in the form of a surprisingly complex array of seemingly redundant, parallel-acting cis-regulatory modules that direct expression to broad, overlapping domains throughout the nervous system. These parallel-acting cis-regulatory modules are responsive to a multitude of distinct trans-acting factors. Neuronal gene expression programs therefore fall into two fundamentally distinct classes. Neuron type-specific genes are generally controlled by discrete and non-redundantly acting regulatory inputs, while pan-neuronal gene expression is controlled by diverse, coincident and seemingly redundant regulatory inputs. PMID:26291158

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

    PubMed

    Ueki, Toshiyuki; Lovley, Derek R

    2010-11-01

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

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

    PubMed Central

    Ueki, Toshiyuki; Lovley, Derek R.

    2010-01-01

    Geobacter species often play an important role in bioremediation of environments contaminated with metals or organics and show promise for harvesting electricity from waste organic matter in microbial fuel cells. The ability of Geobacter species to fix atmospheric nitrogen is an important metabolic feature for these applications. We identified novel regulatory cascades controlling nitrogen-fixation gene expression in Geobacter sulfurreducens. Unlike the regulatory mechanisms known in other nitrogen-fixing microorganisms, nitrogen-fixation gene regulation in G. sulfurreducens is controlled by two two-component His–Asp phosphorelay systems. One of these systems appears to be the master regulatory system that activates transcription of the majority of nitrogen-fixation genes and represses a gene encoding glutamate dehydrogenase during nitrogen fixation. The other system whose expression is directly activated by the master regulatory system appears to control by antitermination the expression of a subset of the nitrogen-fixation genes whose transcription is activated by the master regulatory system and whose promoter contains transcription termination signals. This study provides a new paradigm for nitrogen-fixation gene regulation. PMID:20660485

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

    PubMed

    Raza, Khalid; Alam, Mansaf

    2016-10-01

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

  16. 7SK small nuclear RNA, a multifunctional transcriptional regulatory RNA with gene-specific features.

    PubMed

    Egloff, Sylvain; Studniarek, Cécilia; Kiss, Tamás

    2017-08-18

    The 7SK small nuclear RNA is a multifunctional transcriptional regulatory RNA that controls the nuclear activity of the positive transcription elongation factor b (P-TEFb), specifically targets P-TEFb to the promoter regions of selected protein-coding genes and promotes transcription of RNA polymerase II-specific spliceosomal small nuclear RNA genes.

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

    PubMed

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

    2012-01-01

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

  18. A cloned regulatory gene of Streptomyces lividans can suppress the pigment deficiency phenotype of different developmental mutants.

    PubMed Central

    Stein, D; Cohen, S N

    1989-01-01

    We report here the cloning of a Streptomyces lividans gene that when introduced on a multicopy plasmid vector reversed the pigment deficiency phenotype of several distinct mutants blocked in development, pigment production, or both. Although this gene was shown by restriction enzyme analysis to be similar to a previously cloned afsB-complementing gene of Streptomyces coelicolor, we show that it does not correspond to the S. coelicolor chromosomal locus designated afsB. Thus, the cloned locus, which we propose to rename afsR, appears to complement the AfsB- phenotype by pleiotropic regulatory effects. Images PMID:2703474

  19. Structural components of nuclear integrity with gene regulatory potential.

    PubMed

    Fenelon, Kelli D; Hopyan, Sevan

    2017-10-01

    The nucleus is a mechanosensitive and load-bearing structure. Structural components of the nucleus interact to maintain nuclear integrity and have become subjects of exciting research that is relevant to cell and developmental biology. Here we outline the boundaries of what is known about key architectural elements within the nucleus and highlight their potential structural and transcriptional regulatory functions. Copyright © 2017. Published by Elsevier Ltd.

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

    PubMed

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  2. BLG-e1 - a novel regulatory element in the distal region of the beta-lactoglobulin gene promoter.

    PubMed

    Reichenstein, Moshe; German, Tania; Barash, Itamar

    2005-04-11

    beta-Lactoglobulin (BLG) is a major ruminant milk protein. A regulatory element, termed BLG-e1, was defined in the distal region of the ovine BLG gene promoter. This 299-bp element lacks the established cis-regulatory sequences that affect milk-protein gene expression. Nevertheless, it alters the binding of downstream BLG sequences to histone H4 and the sensitivity of the histone-DNA complexes to trichostatin A treatment. In mammary cells cultured under favorable lactogenic conditions, BLG-e1 acts as a potent, position-independent silencer of BLG/luciferase expression, and similarly affects the promoter activity of the mouse whey acidic protein gene. Intragenic sequences upstream of BLG exon 2 reverse the silencing effect of BLG-e1 in vitro and in transgenic mice.

  3. A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets

    PubMed Central

    2014-01-01

    Background As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. Results A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. Conclusions The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers. PMID:25350697

  4. A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

    PubMed

    Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

    2014-01-01

    As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed Central

    Michailidis, George

    2009-01-01

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

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

    PubMed

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

    2004-07-01

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

  8. Characterization of 5'-regulatory region of human myostatin gene: regulation by dexamethasone in vitro.

    PubMed

    Ma, K; Mallidis, C; Artaza, J; Taylor, W; Gonzalez-Cadavid, N; Bhasin, S

    2001-12-01

    We cloned and characterized a 3.3-kb fragment containing the 5'-regulatory region of the human myostatin gene. The promoter sequence contains putative muscle growth response elements for glucocorticoid, androgen, thyroid hormone, myogenic differentiation factor 1, myocyte enhancer factor 2, peroxisome proliferator-activated receptor, and nuclear factor-kappaB. To identify sites important for myostatin's gene transcription and regulation, eight deletion constructs were placed in C(2)C(12) and L6 skeletal muscle cells. Transcriptional activity of the constructs was found to be significantly higher in myotubes compared with that of myoblasts. To investigate whether glucocorticoids regulate myostatin gene expression, we incubated both cell lines with dexamethasone. On both occasions, dexamethasone dose dependently increased both the promoter's transcriptional activity and the endogenous myostatin expression. The effects of dexamethasone were blocked when the cells were coincubated with the glucocorticoid receptor antagonist RU-486. These findings suggest that glucocorticoids upregulate myostatin expression by inducing gene transcription, possibly through a glucocorticoid receptor-mediated pathway. We speculate that glucocorticoid-associated muscle atrophy might be due in part to the upregulation of myostatin expression.

  9. Divergence of ectodermal and mesodermal gene regulatory network linkages in early development of sea urchins.

    PubMed

    Erkenbrack, Eric M

    2016-11-15

    Developmental gene regulatory networks (GRNs) are assemblages of gene regulatory interactions that direct ontogeny of animal body plans. Studies of GRNs operating in the early development of euechinoid sea urchins have revealed that little appreciable change has occurred since their divergence ∼90 million years ago (mya). These observations suggest that strong conservation of GRN architecture was maintained in early development of the sea urchin lineage. Testing whether this holds for all sea urchins necessitates comparative analyses of echinoid taxa that diverged deeper in geological time. Recent studies highlighted extensive divergence of skeletogenic mesoderm specification in the sister clade of euechinoids, the cidaroids, suggesting that comparative analyses of cidaroid GRN architecture may confer a greater understanding of the evolutionary dynamics of developmental GRNs. Here I report spatiotemporal patterning of 55 regulatory genes and perturbation analyses of key regulatory genes involved in euechinoid oral-aboral patterning of nonskeletogenic mesodermal and ectodermal domains in early development of the cidaroid Eucidaris tribuloides These results indicate that developmental GRNs directing mesodermal and ectodermal specification have undergone marked alterations since the divergence of cidaroids and euechinoids. Notably, statistical and clustering analyses of echinoid temporal gene expression datasets indicate that regulation of mesodermal genes has diverged more markedly than regulation of ectodermal genes. Although research on indirect-developing euechinoid sea urchins suggests strong conservation of GRN circuitry during early embryogenesis, this study indicates that since the divergence of cidaroids and euechinoids, developmental GRNs have undergone significant, cell type-biased alterations.

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

    PubMed

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

    2014-11-26

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

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

    PubMed Central

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

    2014-01-01

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

  12. Finding regulatory modules from gene expression data II

    NASA Astrophysics Data System (ADS)

    Tang, Chao; Kloster, Morten; Wingreen, Ned

    2004-03-01

    We tested the Progressive Iterative Signature Algorithm (PISA) on synthetic data and on a large gene-expression data set for the yeast Saccharomyces cerevisiae. For synthetic data, the false-positive rate for identifying transcriptional modules was extremely low. For the yeast data set of 1012 experimental conditions for 6206 genes, PISA identified a large number of modules, most of which could be readily assigned to specific biological functions. These included many small modules (with as few as five genes) that could not be easily found by ISA. We compared the set of modules we found to the Gene Ontology annotation database and found many significant overlaps. The modules identified by PISA also compare favorably to experimentally and theoretically determined sets of genes regulated by individual transcription factors.

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

    PubMed

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

    2011-05-01

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

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

    PubMed

    Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias

    2013-04-24

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

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

    PubMed Central

    Zainudin, Suhaila; Arif, Shereena M.

    2017-01-01

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

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

    PubMed

    Ozerniuk, I D; Miuge, N S

    2012-01-01

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

  17. Cis-Regulatory Timers for Developmental Gene Expression

    PubMed Central

    Christiaen, Lionel

    2013-01-01

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

  18. A computational framework for gene regulatory network inference that combines multiple methods and datasets

    PubMed Central

    2011-01-01

    Background Reverse engineering in systems biology entails inference of gene regulatory networks from observational data. This data typically include gene expression measurements of wild type and mutant cells in response to a given stimulus. It has been shown that when more than one type of experiment is used in the network inference process the accuracy is higher. Therefore the development of generally applicable and effective methodologies that embed multiple sources of information in a single computational framework is a worthwhile objective. Results This paper presents a new method for network inference, which uses multi-objective optimisation (MOO) to integrate multiple inference methods and experiments. We illustrate the potential of the methodology by combining ODE and correlation-based network inference procedures as well as time course and gene inactivation experiments. Here we show that our methodology is effective for a wide spectrum of data sets and method integration strategies. Conclusions The approach we present in this paper is flexible and can be used in any scenario that benefits from integration of multiple sources of information and modelling procedures in the inference process. Moreover, the application of this method to two case studies representative of bacteria and vertebrate systems has shown potential in identifying key regulators of important biological processes. PMID:21489290

  19. Evolution of Gene Regulatory Networks by Fluctuating Selection and Intrinsic Constraints

    PubMed Central

    Tsuda, Masaki E.; Kawata, Masakado

    2010-01-01

    Various characteristics of complex gene regulatory networks (GRNs) have been discovered during the last decade, e.g., redundancy, exponential indegree distributions, scale-free outdegree distributions, mutational robustness, and evolvability. Although progress has been made in this field, it is not well understood whether these characteristics are the direct products of selection or those of other evolutionary forces such as mutational biases and biophysical constraints. To elucidate the causal factors that promoted the evolution of complex GRNs, we examined the effect of fluctuating environmental selection and some intrinsic constraining factors on GRN evolution by using an individual-based model. We found that the evolution of complex GRNs is remarkably promoted by fixation of beneficial gene duplications under unpredictably fluctuating environmental conditions and that some internal factors inherent in organisms, such as mutational bias, gene expression costs, and constraints on expression dynamics, are also important for the evolution of GRNs. The results indicate that various biological properties observed in GRNs could evolve as a result of not only adaptation to unpredictable environmental changes but also non-adaptive processes owing to the properties of the organisms themselves. Our study emphasizes that evolutionary models considering such intrinsic constraining factors should be used as null models to analyze the effect of selection on GRN evolution. PMID:20700492

  20. An atlas of gene regulatory networks reveals multiple three-gene mechanisms for interpreting morphogen gradients

    PubMed Central

    Cotterell, James; Sharpe, James

    2010-01-01

    The interpretation of morphogen gradients is a pivotal concept in developmental biology, and several mechanisms have been proposed to explain how gene regulatory networks (GRNs) achieve concentration-dependent responses. However, the number of different mechanisms that may exist for cells to interpret morphogens, and the importance of design features such as feedback or local cell–cell communication, is unclear. A complete understanding of such systems will require going beyond a case-by-case analysis of real morphogen interpretation mechanisms and mapping out a complete GRN ‘design space.' Here, we generate a first atlas of design space for GRNs capable of patterning a homogeneous field of cells into discrete gene expression domains by interpreting a fixed morphogen gradient. We uncover multiple very distinct mechanisms distributed discretely across the atlas, thereby expanding the repertoire of morphogen interpretation network motifs. Analyzing this diverse collection of mechanisms also allows us to predict that local cell–cell communication will rarely be responsible for the basic dose-dependent response of morphogen interpretation networks. PMID:21045819

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

    PubMed

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

    2007-01-01

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

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

    PubMed

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

    2013-01-01

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

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

    PubMed

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

    2006-07-01

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

  4. The association between infants' self-regulatory behavior and MAOA gene polymorphism.

    PubMed

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

    2011-09-01

    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 of Chinese infants at 6 months of age. Self-regulation was assessed by observing infants' behavior of orienting visual attention away from a threatening event in the laboratory situation. The results indicated that regulatory behavior was associated with the functional MAOA gene polymorphism in girls, but not boys. Girls with 4/4 genotypes displayed significantly higher regulation than girls with 3/3 and 3/4 genotypes. The present study provided evidence for gender differences on the role of MAOA gene polymorphism in socioemotional functioning in the early years. © 2011 Blackwell Publishing Ltd.

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

    PubMed Central

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

    2016-01-01

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

  6. Inference of gene regulatory networks incorporating multi-source biological knowledge via a state space model with L1 regularization.

    PubMed

    Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

    2014-01-01

    Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid

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

    PubMed Central

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

    2009-01-01

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

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

    SciTech Connect

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

    2003-06-01

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

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

    PubMed Central

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

    2015-01-01

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

  10. Regulatory Elements of the Floral Homeotic Gene AGAMOUS Identified by Phylogenetic Footprinting and ShadowingW⃞

    PubMed Central

    Hong, Ray L.; Hamaguchi, Lynn; Busch, Maximilian A.; Weigel, Detlef

    2003-01-01

    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 species, several other motifs, but not the LFY and WUS binding sites identified previously, are largely invariant. Using reporter gene analyses, we tested six of these motifs and found that they are all functionally important for the 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 demonstrate that sequence-based studies alone are insufficient for a complete identification of cis-regulatory sites. PMID:12782724

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