WorldWideScience

Sample records for cell transcriptional networks

  1. Transcriptional networks in developing and mature B cells.

    Science.gov (United States)

    Matthias, Patrick; Rolink, Antonius G

    2005-06-01

    The development of B cells from haematopoietic stem cells proceeds along a highly ordered, yet flexible, pathway. At multiple steps along this pathway, cells are instructed by transcription factors on how to further differentiate, and several check-points have been identified. These check-points are initial commitment to lymphocytic progenitors, specification of pre-B cells, entry to the peripheral B-cell pool, maturation of B cells and differentiation into plasma cells. At each of these regulatory nodes, there are transcriptional networks that control the outcome, and much progress has recently been made in dissecting these networks. This article reviews our current understanding of this exciting field.

  2. Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

    NARCIS (Netherlands)

    Benevento, Marco; Tonge, Peter D; Puri, Mira C; Hussein, Samer M I; Cloonan, Nicole; Wood, David L; Grimmond, Sean M; Nagy, Andras; Munoz, Javier; Heck, Albert J R

    2014-01-01

    The ectopic expression of Oct4, Klf4, c-Myc and Sox2 (OKMS) transcription factors allows reprogramming of somatic cells into induced pluripotent stem cells (iPSCs). The reprogramming process, which involves a complex network of molecular events, is not yet fully characterized. Here we perform a quan

  3. Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks

    NARCIS (Netherlands)

    Benevento, Marco|info:eu-repo/dai/nl/328200859; Tonge, Peter D; Puri, Mira C; Hussein, Samer M I; Cloonan, Nicole; Wood, David L; Grimmond, Sean M; Nagy, Andras; Munoz, Javier; Heck, Albert J R|info:eu-repo/dai/nl/105189332

    2014-01-01

    The ectopic expression of Oct4, Klf4, c-Myc and Sox2 (OKMS) transcription factors allows reprogramming of somatic cells into induced pluripotent stem cells (iPSCs). The reprogramming process, which involves a complex network of molecular events, is not yet fully characterized. Here we perform a quan

  4. Proteome adaptation in cell reprogramming proceeds via distinct transcriptional networks.

    Science.gov (United States)

    Benevento, Marco; Tonge, Peter D; Puri, Mira C; Hussein, Samer M I; Cloonan, Nicole; Wood, David L; Grimmond, Sean M; Nagy, Andras; Munoz, Javier; Heck, Albert J R

    2014-12-10

    The ectopic expression of Oct4, Klf4, c-Myc and Sox2 (OKMS) transcription factors allows reprogramming of somatic cells into induced pluripotent stem cells (iPSCs). The reprogramming process, which involves a complex network of molecular events, is not yet fully characterized. Here we perform a quantitative mass spectrometry-based analysis to probe in-depth dynamic proteome changes during somatic cell reprogramming. Our data reveal defined waves of proteome resetting, with the first wave occurring 48 h after the activation of the reprogramming transgenes and involving specific biological processes linked to the c-Myc transcriptional network. A second wave of proteome reorganization occurs in a later stage of reprogramming, where we characterize the proteome of two distinct pluripotent cellular populations. In addition, the overlay of our proteome resource with parallel generated -omics data is explored to identify post-transcriptionally regulated proteins involved in key steps during reprogramming.

  5. Transcriptional networks that regulate muscle stem cell function.

    Science.gov (United States)

    Punch, Vincent G; Jones, Andrew E; Rudnicki, Michael A

    2009-01-01

    Muscle stem cells comprise different populations of stem and progenitor cells found in embryonic and adult tissues. A number of signaling and transcriptional networks are responsible for specification and survival of these cell populations and regulation of their behavior during growth and regeneration. Muscle progenitor cells are mostly derived from the somites of developing embryos, while satellite cells are the progenitor cells responsible for the majority of postnatal growth and adult muscle regeneration. In resting muscle, these stem cells are quiescent, but reenter the cell cycle during their activation, whereby they undergo decisions to self-renew, proliferate, or differentiate and fuse into multinucleated myofibers to repair damaged muscle. Regulation of muscle stem cell activity is under the precise control of a number of extrinsic signaling pathways and active transcriptional networks that dictate their behavior, fate, and regenerative potential. Here, we review the networks responsible for these different aspects of muscle stem cell biology and discuss prevalent parallels between mechanisms regulating the activity of embryonic muscle progenitor cells and adult satellite cells.

  6. Transcription factor FOXA2-centered transcriptional regulation network in non-small cell lung cancer

    Energy Technology Data Exchange (ETDEWEB)

    Jang, Sang-Min; An, Joo-Hee; Kim, Chul-Hong; Kim, Jung-Woong, E-mail: jungkim@cau.ac.kr; Choi, Kyung-Hee, E-mail: khchoi@cau.ac.kr

    2015-08-07

    Lung cancer is the leading cause of cancer-mediated death. Although various therapeutic approaches are used for lung cancer treatment, these mainly target the tumor suppressor p53 transcription factor, which is involved in apoptosis and cell cycle arrest. However, p53-targeted therapies have limited application in lung cancer, since p53 is found to be mutated in more than half of lung cancers. In this study, we propose tumor suppressor FOXA2 as an alternative target protein for therapies against lung cancer and reveal a possible FOXA2-centered transcriptional regulation network by identifying new target genes and binding partners of FOXA2 by using various screening techniques. The genes encoding Glu/Asp-rich carboxy-terminal domain 2 (CITED2), nuclear receptor subfamily 0, group B, member 2 (NR0B2), cell adhesion molecule 1 (CADM1) and BCL2-associated X protein (BAX) were identified as putative target genes of FOXA2. Additionally, the proteins including highly similar to heat shock protein HSP 90-beta (HSP90A), heat shock 70 kDa protein 1A variant (HSPA1A), histone deacetylase 1 (HDAC1) and HDAC3 were identified as novel interacting partners of FOXA2. Moreover, we showed that FOXA2-dependent promoter activation of BAX and p21 genes is significantly reduced via physical interactions between the identified binding partners and FOXA2. These results provide opportunities to understand the FOXA2-centered transcriptional regulation network and novel therapeutic targets to modulate this network in p53-deficient lung cancer. - Highlights: • Identification of new target genes of FOXA2. • Identifications of novel interaction proteins of FOXA2. • Construction of FOXA2-centered transcriptional regulatory network in non-small cell lung cancer.

  7. Transcription factor FOXA2-centered transcriptional regulation network in non-small cell lung cancer.

    Science.gov (United States)

    Jang, Sang-Min; An, Joo-Hee; Kim, Chul-Hong; Kim, Jung-Woong; Choi, Kyung-Hee

    2015-08-01

    Lung cancer is the leading cause of cancer-mediated death. Although various therapeutic approaches are used for lung cancer treatment, these mainly target the tumor suppressor p53 transcription factor, which is involved in apoptosis and cell cycle arrest. However, p53-targeted therapies have limited application in lung cancer, since p53 is found to be mutated in more than half of lung cancers. In this study, we propose tumor suppressor FOXA2 as an alternative target protein for therapies against lung cancer and reveal a possible FOXA2-centered transcriptional regulation network by identifying new target genes and binding partners of FOXA2 by using various screening techniques. The genes encoding Glu/Asp-rich carboxy-terminal domain 2 (CITED2), nuclear receptor subfamily 0, group B, member 2 (NR0B2), cell adhesion molecule 1 (CADM1) and BCL2-associated X protein (BAX) were identified as putative target genes of FOXA2. Additionally, the proteins including highly similar to heat shock protein HSP 90-beta (HSP90A), heat shock 70 kDa protein 1A variant (HSPA1A), histone deacetylase 1 (HDAC1) and HDAC3 were identified as novel interacting partners of FOXA2. Moreover, we showed that FOXA2-dependent promoter activation of BAX and p21 genes is significantly reduced via physical interactions between the identified binding partners and FOXA2. These results provide opportunities to understand the FOXA2-centered transcriptional regulation network and novel therapeutic targets to modulate this network in p53-deficient lung cancer.

  8. Intricate Transcriptional Networks of Classical Brown and Beige Fat Cells.

    Science.gov (United States)

    Park, Jun Hong; Hur, Wonhee; Lee, Sean Bong

    2015-01-01

    Brown adipocytes are a specialized cell type that is critical for adaptive thermogenesis, energy homeostasis, and metabolism. In response to cold, both classical brown fat and the newly identified "beige" or "brite" cells are activated by β-adrenergic signaling and catabolize stored lipids and carbohydrates to produce heat via UCP1. Once thought to be non-existent in adults, recent studies have discovered active classical brown and beige fat cells in humans, thus reinvigorating interest in brown and beige adipocytes. This review will focus on the newly discovered transcription factors and microRNAs that specify and orchestrate the classical brown and beige fat cell development.

  9. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  10. The ubiquitous transcription factor CTCF promotes lineage-specific epigenomic remodeling and establishment of transcriptional networks driving cell differentiation.

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    Dubois-Chevalier, Julie; Staels, Bart; Lefebvre, Philippe; Eeckhoute, Jérôme

    2015-01-01

    Cell differentiation relies on tissue-specific transcription factors (TFs) that cooperate to establish unique transcriptomes and phenotypes. However, the role of ubiquitous TFs in these processes remains poorly defined. Recently, we have shown that the CCCTC-binding factor (CTCF) is required for adipocyte differentiation through epigenomic remodelling of adipose tissue-specific enhancers and transcriptional activation of Peroxisome proliferator-activated receptor gamma (PPARG), the main driver of the adipogenic program (PPARG), and its target genes. Here, we discuss how these findings, together with the recent literature, illuminate a functional role for ubiquitous TFs in lineage-determining transcriptional networks.

  11. A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cells.

    Science.gov (United States)

    Niida, Atsushi; Imoto, Seiya; Nagasaki, Masao; Yamaguchi, Rui; Miyano, Satoru

    2010-01-01

    Although microarray technology has revealed transcriptomic diversities underlining various cancer phenotypes, transcriptional programs controlling them have not been well elucidated. To decode transcriptional programs governing cancer transcriptomes, we have recently developed a computational method termed EEM, which searches for expression modules from prescribed gene sets defined by prior biological knowledge like TF binding motifs. In this paper, we extend our EEM approach to predict cancer transcriptional networks. Starting from functional TF binding motifs and expression modules identified by EEM, we predict cancer transcriptional networks containing regulatory TFs, associated GO terms, and interactions between TF binding motifs. To systematically analyze transcriptional programs in broad types of cancer, we applied our EEM-based network prediction method to 122 microarray datasets collected from public databases. The data sets contain about 15000 experiments for tumor samples of various tissue origins including breast, colon, lung etc. This EEM based meta-analysis successfully revealed a prevailing cancer transcriptional network which functions in a large fraction of cancer transcriptomes; they include cell-cycle and immune related sub-networks. This study demonstrates broad applicability of EEM, and opens a way to comprehensive understanding of transcriptional networks in cancer cells.

  12. Computational Analysis of Transcriptional Circuitries in Human Embryonic Stem Cells Reveals Multiple and Independent Networks

    Directory of Open Access Journals (Sweden)

    Xiaosheng Wang

    2014-01-01

    Full Text Available It has been known that three core transcription factors (TFs, NANOG, OCT4, and SOX2, collaborate to form a transcriptional circuitry to regulate pluripotency and self-renewal of human embryonic stem (ES cells. Similarly, MYC also plays an important role in regulating pluripotency and self-renewal of human ES cells. However, the precise mechanism by which the transcriptional regulatory networks control the activity of ES cells remains unclear. In this study, we reanalyzed an extended core network, which includes the set of genes that are cobound by the three core TFs and additional TFs that also bind to these cobound genes. Our results show that beyond the core transcriptional network, additional transcriptional networks are potentially important in the regulation of the fate of human ES cells. Several gene families that encode TFs play a key role in the transcriptional circuitry of ES cells. We also demonstrate that MYC acts independently of the core module in the regulation of the fate of human ES cells, consistent with the established argument. We find that TP53 is a key connecting molecule between the core-centered and MYC-centered modules. This study provides additional insights into the underlying regulatory mechanisms involved in the fate determination of human ES cells.

  13. Characterizing and prototyping genetic networks with cell-free transcription-translation reactions.

    Science.gov (United States)

    Takahashi, Melissa K; Hayes, Clarmyra A; Chappell, James; Sun, Zachary Z; Murray, Richard M; Noireaux, Vincent; Lucks, Julius B

    2015-09-15

    A central goal of synthetic biology is to engineer cellular behavior by engineering synthetic gene networks for a variety of biotechnology and medical applications. The process of engineering gene networks often involves an iterative 'design-build-test' cycle, whereby the parts and connections that make up the network are built, characterized and varied until the desired network function is reached. Many advances have been made in the design and build portions of this cycle. However, the slow process of in vivo characterization of network function often limits the timescale of the testing step. Cell-free transcription-translation (TX-TL) systems offer a simple and fast alternative to performing these characterizations in cells. Here we provide an overview of a cell-free TX-TL system that utilizes the native Escherichia coli TX-TL machinery, thereby allowing a large repertoire of parts and networks to be characterized. As a way to demonstrate the utility of cell-free TX-TL, we illustrate the characterization of two genetic networks: an RNA transcriptional cascade and a protein regulated incoherent feed-forward loop. We also provide guidelines for designing TX-TL experiments to characterize new genetic networks. We end with a discussion of current and emerging applications of cell free systems.

  14. Prediction and testing of novel transcriptional networks regulating embryonic stem cell self-renewal and commitment.

    Science.gov (United States)

    Walker, Emily; Ohishi, Minako; Davey, Ryan E; Zhang, Wen; Cassar, Paul A; Tanaka, Tetsuya S; Der, Sandy D; Morris, Quaid; Hughes, Timothy R; Zandstra, Peter W; Stanford, William L

    2007-06-07

    Stem cell fate is governed by the integration of intrinsic and extrinsic positive and negative signals upon inherent transcriptional networks. To identify novel embryonic stem cell (ESC) regulators and assemble transcriptional networks controlling ESC fate, we performed temporal expression microarray analyses of ESCs after the initiation of commitment and integrated these data with known genome-wide transcription factor binding. Effects of forced under- or overexpression of predicted novel regulators, defined as differentially expressed genes with potential binding sites for known regulators of pluripotency, demonstrated greater than 90% correspondence with predicted function, as assessed by functional and high-content assays of self-renewal. We next assembled 43 theoretical transcriptional networks in ESCs, 82% (23 out of 28 tested) of which were supported by analysis of genome-wide expression in Oct4 knockdown cells. By using this integrative approach, we have formulated novel networks describing gene repression of key developmental regulators in undifferentiated ESCs and successfully predicted the outcomes of genetic manipulation of these networks.

  15. Non-transcriptional regulatory processes shape transcriptional network dynamics

    OpenAIRE

    Ray, J. Christian J; Tabor, Jeffrey J.; Igoshin, Oleg A.

    2011-01-01

    Information about the extra- or intracellular environment is often captured as biochemical signals propagating through regulatory networks. These signals eventually drive phenotypic changes, typically by altering gene expression programs in the cell. Reconstruction of transcriptional regulatory networks has given a compelling picture of bacterial physiology, but transcriptional network maps alone often fail to describe phenotypes. In many cases, the dynamical performance of transcriptional re...

  16. HMGA1 reprograms somatic cells into pluripotent stem cells by inducing stem cell transcriptional networks.

    Directory of Open Access Journals (Sweden)

    Sandeep N Shah

    Full Text Available BACKGROUND: Although recent studies have identified genes expressed in human embryonic stem cells (hESCs that induce pluripotency, the molecular underpinnings of normal stem cell function remain poorly understood. The high mobility group A1 (HMGA1 gene is highly expressed in hESCs and poorly differentiated, stem-like cancers; however, its role in these settings has been unclear. METHODS/PRINCIPAL FINDINGS: We show that HMGA1 is highly expressed in fully reprogrammed iPSCs and hESCs, with intermediate levels in ECCs and low levels in fibroblasts. When hESCs are induced to differentiate, HMGA1 decreases and parallels that of other pluripotency factors. Conversely, forced expression of HMGA1 blocks differentiation of hESCs. We also discovered that HMGA1 enhances cellular reprogramming of somatic cells to iPSCs together with the Yamanaka factors (OCT4, SOX2, KLF4, cMYC - OSKM. HMGA1 increases the number and size of iPSC colonies compared to OSKM controls. Surprisingly, there was normal differentiation in vitro and benign teratoma formation in vivo of the HMGA1-derived iPSCs. During the reprogramming process, HMGA1 induces the expression of pluripotency genes, including SOX2, LIN28, and cMYC, while knockdown of HMGA1 in hESCs results in the repression of these genes. Chromatin immunoprecipitation shows that HMGA1 binds to the promoters of these pluripotency genes in vivo. In addition, interfering with HMGA1 function using a short hairpin RNA or a dominant-negative construct blocks cellular reprogramming to a pluripotent state. CONCLUSIONS: Our findings demonstrate for the first time that HMGA1 enhances cellular reprogramming from a somatic cell to a fully pluripotent stem cell. These findings identify a novel role for HMGA1 as a key regulator of the stem cell state by inducing transcriptional networks that drive pluripotency. Although further studies are needed, these HMGA1 pathways could be exploited in regenerative medicine or as novel therapeutic

  17. Th9 cell development requires a BATF-regulated transcriptional network.

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    Jabeen, Rukhsana; Goswami, Ritobrata; Awe, Olufolakemi; Kulkarni, Aishwarya; Nguyen, Evelyn T; Attenasio, Andrea; Walsh, Daniel; Olson, Matthew R; Kim, Myung H; Tepper, Robert S; Sun, Jie; Kim, Chang H; Taparowsky, Elizabeth J; Zhou, Baohua; Kaplan, Mark H

    2013-11-01

    T helper 9 (Th9) cells are specialized for the production of IL-9, promote allergic inflammation in mice, and are associated with allergic disease in humans. It has not been determined whether Th9 cells express a characteristic transcriptional signature. In this study, we performed microarray analysis to identify genes enriched in Th9 cells compared with other Th subsets. This analysis defined a transcriptional regulatory network required for the expression of a subset of Th9-enriched genes. The activator protein 1 (AP1) family transcription factor BATF (B cell, activating transcription factor–like) was among the genes enriched in Th9 cells and was required for the expression of IL-9 and other Th9-associated genes in both human and mouse T cells. The expression of BATF was increased in Th9 cultures derived from atopic infants compared with Th9 cultures from control infants. T cells deficient in BATF expression had a diminished capacity to promote allergic inflammation compared with wild-type controls. Moreover, mouse Th9 cells ectopically expressing BATF were more efficient at promoting allergic inflammation than control transduced cells. These data indicate that BATF is a central regulator of the Th9 phenotype and contributes to the development of allergic inflammation.

  18. Set7 mediated interactions regulate transcriptional networks in embryonic stem cells.

    Science.gov (United States)

    Tuano, Natasha K; Okabe, Jun; Ziemann, Mark; Cooper, Mark E; El-Osta, Assam

    2016-11-02

    Histone methylation by lysine methyltransferase enzymes regulate the expression of genes implicated in lineage specificity and cellular differentiation. While it is known that Set7 catalyzes mono-methylation of histone and non-histone proteins, the functional importance of this enzyme in stem cell differentiation remains poorly understood. We show Set7 expression is increased during mouse embryonic stem cell (mESC) differentiation and is regulated by the pluripotency factors, Oct4 and Sox2. Transcriptional network analyses reveal smooth muscle (SM) associated genes are subject to Set7-mediated regulation. Furthermore, pharmacological inhibition of Set7 activity confirms this regulation. We observe Set7-mediated modification of serum response factor (SRF) and mono-methylation of histone H4 lysine 4 (H3K4me1) regulate gene expression. We conclude the broad substrate specificity of Set7 serves to control key transcriptional networks in embryonic stem cells.

  19. Schwann cells and their transcriptional network: Evolution of key regulators of peripheral myelination.

    Science.gov (United States)

    Stolt, C Claus; Wegner, Michael

    2016-06-15

    As derivatives of the neural crest, Schwann cells represent a vertebrate invention. Their development and differentiation is under control of a newly constructed, vertebrate-specific regulatory network that contains Sox10, Oct6 and Krox20 as cornerstones and central regulators of peripheral myelination. In this review, we discuss the function and relationship of these transcription factors among each other and in the context of their regulatory network, and present ideas of how neofunctionalization may have helped to recruit them to their novel task in Schwann cells. This article is part of a Special Issue entitled SI: Myelin Evolution.

  20. Non-transcriptional regulatory processes shape transcriptional network dynamics.

    Science.gov (United States)

    Ray, J Christian J; Tabor, Jeffrey J; Igoshin, Oleg A

    2011-10-11

    Information about the extra- or intracellular environment is often captured as biochemical signals that propagate through regulatory networks. These signals eventually drive phenotypic changes, typically by altering gene expression programmes in the cell. Reconstruction of transcriptional regulatory networks has given a compelling picture of bacterial physiology, but transcriptional network maps alone often fail to describe phenotypes. Cellular response dynamics are ultimately determined by interactions between transcriptional and non-transcriptional networks, with dramatic implications for physiology and evolution. Here, we provide an overview of non-transcriptional interactions that can affect the performance of natural and synthetic bacterial regulatory networks.

  1. Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis.

    Science.gov (United States)

    Moignard, Victoria; Macaulay, Iain C; Swiers, Gemma; Buettner, Florian; Schütte, Judith; Calero-Nieto, Fernando J; Kinston, Sarah; Joshi, Anagha; Hannah, Rebecca; Theis, Fabian J; Jacobsen, Sten Eirik; de Bruijn, Marella F; Göttgens, Berthold

    2013-04-01

    Cellular decision-making is mediated by a complex interplay of external stimuli with the intracellular environment, in particular transcription factor regulatory networks. Here we have determined the expression of a network of 18 key haematopoietic transcription factors in 597 single primary blood stem and progenitor cells isolated from mouse bone marrow. We demonstrate that different stem/progenitor populations are characterized by distinctive transcription factor expression states, and through comprehensive bioinformatic analysis reveal positively and negatively correlated transcription factor pairings, including previously unrecognized relationships between Gata2, Gfi1 and Gfi1b. Validation using transcriptional and transgenic assays confirmed direct regulatory interactions consistent with a regulatory triad in immature blood stem cells, where Gata2 may function to modulate cross-inhibition between Gfi1 and Gfi1b. Single-cell expression profiling therefore identifies network states and allows reconstruction of network hierarchies involved in controlling stem cell fate choices, and provides a blueprint for studying both normal development and human disease.

  2. Regulation of a transcription factor network by Cdk1 coordinates late cell cycle gene expression.

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    Landry, Benjamin D; Mapa, Claudine E; Arsenault, Heather E; Poti, Kristin E; Benanti, Jennifer A

    2014-05-02

    To maintain genome stability, regulators of chromosome segregation must be expressed in coordination with mitotic events. Expression of these late cell cycle genes is regulated by cyclin-dependent kinase (Cdk1), which phosphorylates a network of conserved transcription factors (TFs). However, the effects of Cdk1 phosphorylation on many key TFs are not known. We find that elimination of Cdk1-mediated phosphorylation of four S-phase TFs decreases expression of many late cell cycle genes, delays mitotic progression, and reduces fitness in budding yeast. Blocking phosphorylation impairs degradation of all four TFs. Consequently, phosphorylation-deficient mutants of the repressors Yox1 and Yhp1 exhibit increased promoter occupancy and decreased expression of their target genes. Interestingly, although phosphorylation of the transcriptional activator Hcm1 on its N-terminus promotes its degradation, phosphorylation on its C-terminus is required for its activity, indicating that Cdk1 both activates and inhibits a single TF. We conclude that Cdk1 promotes gene expression by both activating transcriptional activators and inactivating transcriptional repressors. Furthermore, our data suggest that coordinated regulation of the TF network by Cdk1 is necessary for faithful cell division.

  3. Mapping Yeast Transcriptional Networks

    OpenAIRE

    Hughes, Timothy R; de Boer, Carl G.

    2013-01-01

    The term “transcriptional network” refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face....

  4. Inference of Transcriptional Network for Pluripotency in Mouse Embryonic Stem Cells

    Science.gov (United States)

    Aburatani, S.

    2015-01-01

    In embryonic stem cells, various transcription factors (TFs) maintain pluripotency. To gain insights into the regulatory system controlling pluripotency, I inferred the regulatory relationships between the TFs expressed in ES cells. In this study, I applied a method based on structural equation modeling (SEM), combined with factor analysis, to 649 expression profiles of 19 TF genes measured in mouse Embryonic Stem Cells (ESCs). The factor analysis identified 19 TF genes that were regulated by several unmeasured factors. Since the known cell reprogramming TF genes (Pou5f1, Sox2 and Nanog) are regulated by different factors, each estimated factor is considered to be an input for signal transduction to control pluripotency in mouse ESCs. In the inferred network model, TF proteins were also arranged as unmeasured factors that control other TFs. The interpretation of the inferred network model revealed the regulatory mechanism for controlling pluripotency in ES cells.

  5. Langerhans cells are generated by two distinct PU.1-dependent transcriptional networks.

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    Chopin, Michaël; Seillet, Cyril; Chevrier, Stéphane; Wu, Li; Wang, Hongsheng; Morse, Herbert C; Belz, Gabrielle T; Nutt, Stephen L

    2013-12-16

    Langerhans cells (LCs) are the unique dendritic cells found in the epidermis. While a great deal of attention has focused on defining the developmental origins of LCs, reports addressing the transcriptional network ruling their differentiation remain sparse. We addressed the function of a group of key DC transcription factors-PU.1, ID2, IRF4, and IRF8-in the establishment of the LC network. We show that although steady-state LC homeostasis depends on PU.1 and ID2, the latter is dispensable for bone marrow-derived LCs. PU.1 controls LC differentiation by regulating the expression of the critical TGF-β responsive transcription factor RUNX3. PU.1 directly binds to the Runx3 regulatory elements in a TGF-β-dependent manner, whereas ectopic expression of RUNX3 rescued LC differentiation in the absence of PU.1 and promoted LC differentiation from PU.1-sufficient progenitors. These findings highlight the dual molecular network underlying LC differentiation, and show the central role of PU.1 in these processes.

  6. Uncovering early response of gene regulatory networks in ES cells by systematic induction of transcription factors

    Science.gov (United States)

    Nishiyama, Akira; Xin, Li; Sharov, Alexei A.; Thomas, Marshall; Mowrer, Gregory; Meyers, Emily; Piao, Yulan; Mehta, Samir; Yee, Sarah; Nakatake, Yuhki; Stagg, Carole; Sharova, Lioudmila; Correa-Cerro, Lina S.; Bassey, Uwem; Hoang, Hien; Kim, Eugene; Tapnio, Richard; Qian, Yong; Dudekula, Dawood; Zalzman, Michal; Li, Manxiang; Falco, Geppino; Yang, Hsih-Te; Lee, Sung-Lim; Monti, Manuela; Stanghellini, Ilaria; Islam, Md. Nurul; Nagaraja, Ramaiah; Goldberg, Ilya; Wang, Weidong; Longo, Dan L.; Schlessinger, David; Ko, Minoru S. H.

    2009-01-01

    SUMMARY To examine transcription factor (TF) network(s), we created mouse ES cell lines, in each of which one of 50 TFs tagged with a FLAG moiety is inserted into a ubiquitously controllable tetracycline-repressible locus. Of the 50 TFs, Cdx2 provoked the most extensive transcriptome perturbation in ES cells, followed by Esx1, Sox9, Tcf3, Klf4, and Gata3. ChIP-Seq revealed that CDX2 binds to promoters of up-regulated target genes. By contrast, genes down-regulated by CDX2 did not show CDX2 binding, but were enriched with binding sites for POU5F1, SOX2, and NANOG. Genes with binding sites for these core TFs were also down-regulated by the induction of at least 15 other TFs, suggesting a common initial step for ES cell differentiation mediated by interference with the binding of core TFs to their target genes. These ES cell lines provide a fundamental resource to study biological networks in ES cells and mice. PMID:19796622

  7. Transcriptional network profile on synovial fluid T cells in psoriatic arthritis.

    Science.gov (United States)

    Fiocco, Ugo; Martini, Veronica; Accordi, Benedetta; Caso, Francesco; Costa, Luisa; Oliviero, Francesca; Scanu, Anna; Facco, Monica; Boso, Daniele; Gatto, Mariele; Felicetti, Mara; Frallonardo, Paola; Ramonda, Roberta; Piva, Lucia; Zambello, Renato; Agostini, Carlo; Scarpa, Raffaele; Basso, Giuseppe; Semenzato, Gianpietro; Dayer, Jean-Michel; Punzi, Leonardo; Doria, Andrea

    2015-09-01

    The objective of the study was to quantify the transcriptional profile, as the main T cell lineage-transcription factors on synovial fluid (SF) T cells, in relation to SF cytokines and T cell frequencies (%) of psoriatic arthritis (PsA) patients. Reverse phase protein array was employed to identify interleukin (IL)-23Rp19-, FOXP3- and related orphan receptor gamma T (RORγt)- protein and Janus associated tyrosine kinases 1 (JAK1), signal transducer and activator and transcription 1 (STAT1), STAT3 and STAT5 phosphoproteins in total T cell lysates from SF of PsA patients. IL-1β, IL-2, IL-6, IL-21 and interferon (INF)-γ were measured using a multiplex bead immunoassay in SF from PsA patients and peripheral blood (PB) from healthy controls (HC). Frequencies of CD4(+)CD25(-), CD4(+)CD25(high) FOXP3(+) and CD4(+)CD25(high) CD127(low) Treg, and either mean fluorescence intensity (MFI) of FOXP3(+) on CD4(+) Treg or MFI of classic IL-6 receptor (IL-6R) α expression on CD4(+)CD25(-) helper/effector T cells (Th/eff) and Treg cells, were quantified in SF of PsA patients and in PB from HC by flow cytometry (FC). In PsA SF samples, IL-2, IL-21 and IFN-γ were not detectable, whereas IL-6 and IL-1β levels were higher than in SF of non-inflammatory osteoarthritis patients. Higher levels of IL-23R-, FOXP3- and RORγt proteins and JAK1, STAT1, STAT3 and STAT5 were found in total T cells from SF of PsA patients compared with PB from HC. Direct correlations between JAK1 Y1022/Y1023 and STAT5 Y694, and STAT3 Y705 and IL6, were found in SF of PsA patients. Increased proportion of CD4(+)CD25(high) FOXP3(+) and CD4(+)CD25(high) CD127(low) Treg cells and brighter MFI of IL-6Rα were observed both on CD4(+)CD25(high)- and CD4(+)CD25(-) T cells in PsA SF. The study showed a distinctive JAK1/STAT3/STAT5 transcriptional network on T cells in the joint microenvironment, outlining the interplay of IL-6, IL-23, IL-1β and γC cytokines in the polarization and plasticity of Th17 and Treg cells

  8. Sox2 transcription network acts as a molecular switch to regulate properties of neural stem cells

    Institute of Scientific and Technical Information of China (English)

    Koji; Shimozaki

    2014-01-01

    Neural stem cells(NSCs) contribute to ontogeny by producing neurons at the appropriate time and location. Neurogenesis from NSCs is also involved in various biological functions in adults. Thus, NSCs continue to exert their effects throughout the lifespan of the organism. The mechanism regulating the core functional properties of NSCs is governed by intra- and extracellular signals. Among the transcription factors that serve as molecular switches, Sox2 is considered a key factor in NSCs. Sox2 forms a core network with partner factors, thereby functioning as a molecular switch. This review discusses how the network of Sox2 partner and target genes illustrates the molecular characteristics of the mechanism underlying the self-renewal and multipotency of NSCs.

  9. A transcription factor network controls cell migration and fate decisions in the developing zebrafish pineal complex

    Science.gov (United States)

    Clanton, Joshua A.; Dean, Benjamin J.; Gamse, Joshua T.

    2016-01-01

    The zebrafish pineal complex consists of four cell types (rod and cone photoreceptors, projection neurons and parapineal neurons) that are derived from a single pineal complex anlage. After specification, parapineal neurons migrate unilaterally away from the rest of the pineal complex whereas rods, cones and projection neurons are non-migratory. The transcription factor Tbx2b is important for both the correct number and migration of parapineal neurons. We find that two additional transcription factors, Flh and Nr2e3, negatively regulate parapineal formation. Flh induces non-migratory neuron fates and limits the extent of parapineal specification, in part by activation of Nr2e3 expression. Tbx2b is positively regulated by Flh, but opposes Flh action during specification of parapineal neurons. Loss of parapineal neuron specification in Tbx2b-deficient embryos can be partially rescued by loss of Nr2e3 or Flh function; however, parapineal migration absolutely requires Tbx2b activity. We conclude that cell specification and migration in the pineal complex are regulated by a network of at least three transcription factors. PMID:27317804

  10. Role of ALKBH1 in the Core Transcriptional Network of Embryonic Stem Cells

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    Rune Ougland

    2016-01-01

    Full Text Available Background/Aims: ALKBH1, an AlkB homologue in the 2-oxoglutarate and Fe2+ dependent hydroxylase family, is a histone dioxygenase that removes methyl groups from histone H2A. Studies of transgenic mice lacking Alkbh1 reveal that most Alkbh1-/- embryos die during embryonic development. Embryonic stem cells (ESCs derived from these mice have prolonged expression of pluripotency markers and delayed induction of genes involved in neural differentiation, indicating that ALKBH1 is involved in regulation of pluripotency and differentiation. The aim of this study was to further investigate the role ALKBH1 in early development. Methods: Double-filter methods for nitrocellulose-filter binding, dot blot, enzyme-linked immunosorbent assay (ELISA, immonocytochemistry, cell culture and differentiation of mouse ESCs, Co-IP and miRNA analysis. Results: We found that SOX2 and NANOG bind the ALKBH1 promoter, and we identified protein-protein interactions between ALKBH1 and these core transcription factors of the pluripotency network. Furthermore, lack of ALKBH1 affected the expression of developmentally important miRNAs, which are involved in the regulation of NANOG, SOX2 and neural differentiation. Conclusion: Our results suggest that ALKBH1 interacts with the core transcriptional pluripotency network of ESCs and is involved in regulation of pluripotency and differentiation.

  11. System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

    Science.gov (United States)

    Sakata, Katsumi; Ohyanagi, Hajime; Sato, Shinji; Nobori, Hiroya; Hayashi, Akiko; Ishii, Hideshi; Daub, Carsten O.; Kawai, Jun; Suzuki, Harukazu; Saito, Toshiyuki

    2015-02-01

    We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

  12. Mapping yeast transcriptional networks.

    Science.gov (United States)

    Hughes, Timothy R; de Boer, Carl G

    2013-09-01

    The term "transcriptional network" refers to the mechanism(s) that underlies coordinated expression of genes, typically involving transcription factors (TFs) binding to the promoters of multiple genes, and individual genes controlled by multiple TFs. A multitude of studies in the last two decades have aimed to map and characterize transcriptional networks in the yeast Saccharomyces cerevisiae. We review the methodologies and accomplishments of these studies, as well as challenges we now face. For most yeast TFs, data have been collected on their sequence preferences, in vivo promoter occupancy, and gene expression profiles in deletion mutants. These systematic studies have led to the identification of new regulators of numerous cellular functions and shed light on the overall organization of yeast gene regulation. However, many yeast TFs appear to be inactive under standard laboratory growth conditions, and many of the available data were collected using techniques that have since been improved. Perhaps as a consequence, comprehensive and accurate mapping among TF sequence preferences, promoter binding, and gene expression remains an open challenge. We propose that the time is ripe for renewed systematic efforts toward a complete mapping of yeast transcriptional regulatory mechanisms.

  13. AP-1 is a component of the transcriptional network regulated by GSK-3 in quiescent cells.

    Directory of Open Access Journals (Sweden)

    John W Tullai

    Full Text Available BACKGROUND: The protein kinase GSK-3 is constitutively active in quiescent cells in the absence of growth factor signaling. Previously, we identified a set of genes that required GSK-3 to maintain their repression during quiescence. Computational analysis of the upstream sequences of these genes predicted transcription factor binding sites for CREB, NFκB and AP-1. In our previous work, contributions of CREB and NFκB were examined. In the current study, the AP-1 component of the signaling network in quiescent cells was explored. METHODOLOGY/PRINCIPAL FINDINGS: Using chromatin immunoprecipitation analysis, two AP-1 family members, c-Jun and JunD, bound to predicted upstream regulatory sequences in 8 of the 12 GSK-3-regulated genes. c-Jun was phosphorylated on threonine 239 by GSK-3 in quiescent cells, consistent with previous studies demonstrating inhibition of c-Jun by GSK-3. Inhibition of GSK-3 attenuated this phosphorylation, resulting in the stabilization of c-Jun. The association of c-Jun with its target sequences was increased by growth factor stimulation as well as by direct GSK-3 inhibition. The physiological role for c-Jun was also confirmed by siRNA inhibition of gene induction. CONCLUSIONS/SIGNIFICANCE: These results indicate that inhibition of c-Jun by GSK-3 contributes to the repression of growth factor-inducible genes in quiescent cells. Together, AP-1, CREB and NFκB form an integrated transcriptional network that is largely responsible for maintaining repression of target genes downstream of GSK-3 signaling.

  14. Single-cell Transcriptional Analysis Reveals Novel Neuronal Phenotypes and Interaction Networks involved In the Central Circadian Clock

    Directory of Open Access Journals (Sweden)

    James Park

    2016-10-01

    Full Text Available Single-cell heterogeneity confounds efforts to understand how a population of cells organizes into cellular networks that underlie tissue-level function. This complexity is prominent in the mammalian suprachiasmatic nucleus (SCN. Here, individual neurons exhibit a remarkable amount of asynchronous behavior and transcriptional heterogeneity. However, SCN neurons are able to generate precisely coordinated synaptic and molecular outputs that synchronize the body to a common circadian cycle by organizing into cellular networks. To understand this emergent cellular network property, it is important to reconcile single-neuron heterogeneity with network organization. In light of recent studies suggesting that transcriptionally heterogeneous cells organize into distinct cellular phenotypes, we characterized the transcriptional, spatial, and functional organization of 352 SCN neurons from mice experiencing phase-shifts in their circadian cycle. Using the community structure detection method and multivariate analytical techniques, we identified previously undescribed neuronal phenotypes that are likely to participate in regulatory networks with known SCN cell types. Based on the newly discovered neuronal phenotypes, we developed a data-driven neuronal network structure in which multiple cell types interact through known synaptic and paracrine signaling mechanisms. These results provide a basis from which to interpret the functional variability of SCN neurons and describe methodologies towards understanding how a population of heterogeneous single cells organizes into cellular networks that underlie tissue-level function.

  15. Transcriptional networks in single perivascular cells sorted from human adipose tissue reveal a hierarchy of mesenchymal stem cells.

    Science.gov (United States)

    Hardy, W Reef; Moldovan, Nicanor I; Moldovan, Leni; Livak, Kenneth J; Datta; Goswami, Chirayu; Corselli, Mirko; Traktuev, Dmitry O; Murray, Iain R; Péault, Bruno; March, Keith

    2017-02-24

    Adipose tissue is a rich source of multipotent mesenchymal stem-like cells, located in the perivascular niche. Based on their surface markers, these have been assigned to two main categories: CD34+CD31-CD45-CD146- cells (adventitial stromal/stem cells, ASCs), and CD146+CD31-CD34-CD45- cells (pericytes, PCs). These populations display heterogeneity of unknown significance. We hypothesized that aldehyde dehydrogenase (ALDH) activity, a functional marker of primitivity, could help to better define ASC and PC subclasses. To this end, the stromal vascular fraction from a human lipoaspirate was simultaneously stained with fluorescent antibodies to CD31, CD45, CD34, and CD146 antigens and the ALDH substrate Aldefluor®, then sorted by FACS. Individual ASCs (n=67) and PCs (n=73) selected from the extremities of the ALDH-staining spectrum were transcriptionally profiled by Fluidigm single-cell quantitative PCR for a predefined set (n=429) of marker genes. To these single-cell data, we applied differential expression and principal component and clustering analysis, as well as an original gene co-expression network reconstruction algorithm. Despite the stochasticity at the single-cell level, covariation gene expression analysis yielded multiple network connectivity parameters suggesting that these perivascular progenitor cell subclasses possess the following order of maturity: i) ALDH(br) ASC (most primitive); ii) ALDH(dim) ASC; iii) ALDH(br) PC; iv) ALDH(dim) PC (least primitive). This order was independently supported by specific combinations of class-specific expressed genes and further confirmed by the analysis of associated signaling pathways. In conclusion, single-cell transcriptional analysis of four populations isolated from fat by surface markers and enzyme activity suggests a developmental hierarchy among perivascular mesenchymal stem cells supported by markers and co-expression networks. This article is protected by copyright. All rights reserved.

  16. Activin/Nodal signaling controls divergent transcriptional networks in human embryonic stem cells and in endoderm progenitors.

    Science.gov (United States)

    Brown, Stephanie; Teo, Adrian; Pauklin, Siim; Hannan, Nicholas; Cho, Candy H-H; Lim, Bing; Vardy, Leah; Dunn, N Ray; Trotter, Matthew; Pedersen, Roger; Vallier, Ludovic

    2011-08-01

    Activin/Nodal signaling is necessary to maintain pluripotency of human embryonic stem cells (hESCs) and to induce their differentiation toward endoderm. However, the mechanisms by which Activin/Nodal signaling achieves these opposite functions remain unclear. To unravel these mechanisms, we examined the transcriptional network controlled in hESCs by Smad2 and Smad3, which represent the direct effectors of Activin/Nodal signaling. These analyses reveal that Smad2/3 participate in the control of the core transcriptional network characterizing pluripotency, which includes Oct-4, Nanog, FoxD3, Dppa4, Tert, Myc, and UTF1. In addition, similar experiments performed on endoderm cells confirm that a broad part of the transcriptional network directing differentiation is downstream of Smad2/3. Therefore, Activin/Nodal signaling appears to control divergent transcriptional networks in hESCs and in endoderm. Importantly, we observed an overlap between the transcriptional network downstream of Nanog and Smad2/3 in hESCs; whereas, functional studies showed that both factors cooperate to control the expression of pluripotency genes. Therefore, the effect of Activin/Nodal signaling on pluripotency and differentiation could be dictated by tissue specific Smad2/3 partners such as Nanog, explaining the mechanisms by which signaling pathways can orchestrate divergent cell fate decisions.

  17. Transcription Factor Networks in Drosophila melanogaster

    Directory of Open Access Journals (Sweden)

    David Y. Rhee

    2014-09-01

    Full Text Available Specific cellular fates and functions depend on differential gene expression, which occurs primarily at the transcriptional level and is controlled by complex regulatory networks of transcription factors (TFs. TFs act through combinatorial interactions with other TFs, cofactors, and chromatin-remodeling proteins. Here, we define protein-protein interactions using a coaffinity purification/mass spectrometry method and study 459 Drosophila melanogaster transcription-related factors, representing approximately half of the established catalog of TFs. We probe this network in vivo, demonstrating functional interactions for many interacting proteins, and test the predictive value of our data set. Building on these analyses, we combine regulatory network inference models with physical interactions to define an integrated network that connects combinatorial TF protein interactions to the transcriptional regulatory network of the cell. We use this integrated network as a tool to connect the functional network of genetic modifiers related to mastermind, a transcriptional cofactor of the Notch pathway.

  18. Transcriptional networks in plasmacytoid dendritic cells stimulated with synthetic TLR 7 agonists

    Directory of Open Access Journals (Sweden)

    Vasilakos John P

    2007-10-01

    Full Text Available Abstract Background Plasmacytoid Dendritic Cells (pDC comprise approximately 0.2 to 0.8% of the blood mononuclear cells and are the primary type 1 interferon (IFN, producing cells, secreting high levels of IFN in response to viral infections. Plasmacytoid dendritic cells express predominantly TLRs 7 & 9, making them responsive to ssRNA and CpG DNA. The objective of this study was to evaluate the molecular and cellular processes altered upon stimulation of pDC with synthetic TLR 7 and TLR 7/8 agonists. To this end, we evaluated changes in global gene expression upon stimulation of 99.9% pure human pDC with the TLR7 selective agonists 3M-852A, and the TLR7/8 agonist 3M-011. Results Global gene expression was evaluated using the Affymetrix U133A GeneChip® and selected genes were confirmed using real time TaqMan® RTPCR. The gene expression profiles of the two agonists were similar indicating that changes in gene expression were solely due to stimulation through TLR7. Type 1 interferons were among the highest induced genes and included IFNB and multiple IFNα subtypes, IFNα2, α5, α6, α8, α1/13, α10, α14, α16, α17, α21. A large number of chemokines and co-stimulatory molecules as well as the chemokine receptor CCR7 were increased in expression indicating maturation and change in the migratory ability of pDC. Induction of an antiviral state was shown by the expression of several IFN-inducible genes with known anti-viral activity. Further analysis of the data using the pathway analysis tool MetaCore gave insight into molecular and cellular processes impacted. The analysis revealed transcription networks that show increased expression of signaling components in TLR7 and TLR3 pathways, and the cytosolic anti-viral pathway regulated by RIG1 and MDA5, suggestive of optimization of an antiviral state targeted towards RNA viruses. The analysis also revealed increased expression of a network of genes important for protein ISGylation as well as an

  19. Genome-wide analysis of LXRα activation reveals new transcriptional networks in human atherosclerotic foam cells.

    Science.gov (United States)

    Feldmann, Radmila; Fischer, Cornelius; Kodelja, Vitam; Behrens, Sarah; Haas, Stefan; Vingron, Martin; Timmermann, Bernd; Geikowski, Anne; Sauer, Sascha

    2013-04-01

    Increased physiological levels of oxysterols are major risk factors for developing atherosclerosis and cardiovascular disease. Lipid-loaded macrophages, termed foam cells, are important during the early development of atherosclerotic plaques. To pursue the hypothesis that ligand-based modulation of the nuclear receptor LXRα is crucial for cell homeostasis during atherosclerotic processes, we analysed genome-wide the action of LXRα in foam cells and macrophages. By integrating chromatin immunoprecipitation-sequencing (ChIP-seq) and gene expression profile analyses, we generated a highly stringent set of 186 LXRα target genes. Treatment with the nanomolar-binding ligand T0901317 and subsequent auto-regulatory LXRα activation resulted in sequence-dependent sharpening of the genome-binding patterns of LXRα. LXRα-binding loci that correlated with differential gene expression revealed 32 novel target genes with potential beneficial effects, which in part explained the implications of disease-associated genetic variation data. These observations identified highly integrated LXRα ligand-dependent transcriptional networks, including the APOE/C1/C4/C2-gene cluster, which contribute to the reversal of cholesterol efflux and the dampening of inflammation processes in foam cells to prevent atherogenesis.

  20. The histone acetyltransferase MOF is a key regulator of the embryonic stem cell core transcriptional network.

    Science.gov (United States)

    Li, Xiangzhi; Li, Li; Pandey, Ruchi; Byun, Jung S; Gardner, Kevin; Qin, Zhaohui; Dou, Yali

    2012-08-03

    Pluripotent embryonic stem cells (ESCs) maintain self-renewal and the potential for rapid response to differentiation cues. Both ESC features are subject to epigenetic regulation. Here we show that the histone acetyltransferase Mof plays an essential role in the maintenance of ESC self-renewal and pluripotency. ESCs with Mof deletion lose characteristic morphology, alkaline phosphatase (AP) staining, and differentiation potential. They also have aberrant expression of the core transcription factors Nanog, Oct4, and Sox2. Importantly, the phenotypes of Mof null ESCs can be partially suppressed by Nanog overexpression, supporting the idea that Mof functions as an upstream regulator of Nanog in ESCs. Genome-wide ChIP-sequencing and transcriptome analyses further demonstrate that Mof is an integral component of the ESC core transcriptional network and that Mof primes genes for diverse developmental programs. Mof is also required for Wdr5 recruitment and H3K4 methylation at key regulatory loci, highlighting the complexity and interconnectivity of various chromatin regulators in ESCs.

  1. Linkage of E2F1 transcriptional network and cell proliferation with respiratory chain activity in breast cancer cells.

    Science.gov (United States)

    Mori, Kazunori; Uchida, Tetsu; Fukumura, Motonori; Tamiya, Shigetoshi; Higurashi, Masato; Sakai, Hirosato; Ishikawa, Fumihiro; Shibanuma, Motoko

    2016-07-01

    Mitochondria are multifunctional organelles; they have been implicated in various aspects of tumorigenesis. In this study, we investigated a novel role of the basal electron transport chain (ETC) activity in cell proliferation by inhibiting mitochondrial replication and transcription (mtR/T) using pharmacological and genetic interventions, which depleted mitochondrial DNA/RNA, thereby inducing ETC deficiency. Interestingly, mtR/T inhibition did not decrease ATP levels despite deficiency in ETC activity in different cell types, including MDA-MB-231 breast cancer cells, but it severely impeded cell cycle progression, specifically progression during G2 and/or M phases in the cancer cells. Under these conditions, the expression of a group of cell cycle regulators was downregulated without affecting the growth signaling pathway. Further analysis suggested that the transcriptional network organized by E2F1 was significantly affected because of the downregulation of E2F1 in response to ETC deficiency, which eventually resulted in the suppression of cell proliferation. Thus, in this study, the E2F1-mediated ETC-dependent mechanism has emerged as the regulatory mechanism of cell cycle progression. In addition to E2F1, FOXM1 and BMYB were also downregulated, which contributed specifically to the defects in G2 and/or M phase progression. Thus, ETC-deficient cancer cells lost their growing ability, including their tumorigenic potential in vivo. ETC deficiency abolished the production of reactive oxygen species (ROS) from the mitochondria and a mitochondria-targeted antioxidant mimicked the deficiency, thereby suggesting that ETC activity signaled through ROS production. In conclusion, this novel coupling between ETC activity and cell cycle progression may be an important mechanism for coordinating cell proliferation and metabolism.

  2. Transcriptional Regulatory Networks Activated by PI3K and ERK Transduced Growth Signals in Human Glioblastoma Cells

    Institute of Scientific and Technical Information of China (English)

    Peter M. Haverty; Zhi-Ping Weng; Ulla Hansen

    2005-01-01

    Determining how cells regulate their transcriptional response to extracellular signals is key to the understanding of complex eukaryotic systems. This study was initiated with the goals of furthering the study of mammalian transcriptional regulation and analyzing the relative benefits of related computational methodologies. One dataset available for such an analysis involved gene expression profiling of the early growth factor response to platelet derived growth factor (PDGF)in a human glioblastoma cell line; this study differentiated genes whose expression was regulated by signaling through the phosphoinositide-3-kinase (PI3K) versus the extracellular-signal regulated kinase (ERK) pathways. We have compared the inferred transcription factors from this previous study with additional predictions of regulatory transcription factors using two alternative promoter sequence analysis techniques. This comparative analysis, in which the algorithms predict overlapping,although not identical, sets of factors, argues for meticulous benchmarking of promoter sequence analysis methods to determine the positive and negative attributes that contribute to their varying results. Finally, we inferred transcriptional regulatory networks deriving from various signaling pathways using the CARRIE program suite. These networks not only included previously described transcriptional features of the response to growth signals, but also predicted new regulatory features for the propagation and modulation of the growth signal.

  3. Small-molecule RORγt antagonists inhibit T helper 17 cell transcriptional network by divergent mechanisms.

    Science.gov (United States)

    Xiao, Sheng; Yosef, Nir; Yang, Jianfei; Wang, Yonghui; Zhou, Ling; Zhu, Chen; Wu, Chuan; Baloglu, Erkan; Schmidt, Darby; Ramesh, Radha; Lobera, Mercedes; Sundrud, Mark S; Tsai, Pei-Yun; Xiang, Zhijun; Wang, Jinsong; Xu, Yan; Lin, Xichen; Kretschmer, Karsten; Rahl, Peter B; Young, Richard A; Zhong, Zhong; Hafler, David A; Regev, Aviv; Ghosh, Shomir; Marson, Alexander; Kuchroo, Vijay K

    2014-04-17

    We identified three retinoid-related orphan receptor gamma t (RORγt)-specific inhibitors that suppress T helper 17 (Th17) cell responses, including Th17-cell-mediated autoimmune disease. We systemically characterized RORγt binding in the presence and absence of drugs with corresponding whole-genome transcriptome sequencing. RORγt acts as a direct activator of Th17 cell signature genes and a direct repressor of signature genes from other T cell lineages; its strongest transcriptional effects are on cis-regulatory sites containing the RORα binding motif. RORγt is central in a densely interconnected regulatory network that shapes the balance of T cell differentiation. Here, the three inhibitors modulated the RORγt-dependent transcriptional network to varying extents and through distinct mechanisms. Whereas one inhibitor displaced RORγt from its target loci, the other two inhibitors affected transcription predominantly without removing DNA binding. Our work illustrates the power of a system-scale analysis of transcriptional regulation to characterize potential therapeutic compounds that inhibit pathogenic Th17 cells and suppress autoimmunity.

  4. Fgf and Esrrb integrate epigenetic and transcriptional networks that regulate self-renewal of trophoblast stem cells.

    Science.gov (United States)

    Latos, Paulina A; Goncalves, Angela; Oxley, David; Mohammed, Hisham; Turro, Ernest; Hemberger, Myriam

    2015-07-24

    Esrrb (oestrogen-related receptor beta) is a transcription factor implicated in embryonic stem (ES) cell self-renewal, yet its knockout causes intrauterine lethality due to defects in trophoblast development. Here we show that in trophoblast stem (TS) cells, Esrrb is a downstream target of fibroblast growth factor (Fgf) signalling and is critical to drive TS cell self-renewal. In contrast to its occupancy of pluripotency-associated loci in ES cells, Esrrb sustains the stemness of TS cells by direct binding and regulation of TS cell-specific transcription factors including Elf5 and Eomes. To elucidate the mechanisms whereby Esrrb controls the expression of its targets, we characterized its TS cell-specific interactome using mass spectrometry. Unlike in ES cells, Esrrb interacts in TS cells with the histone demethylase Lsd1 and with the RNA Polymerase II-associated Integrator complex. Our findings provide new insights into both the general and context-dependent wiring of transcription factor networks in stem cells by master transcription factors.

  5. Network analysis of the transcriptional pattern of young and old cells of Escherichia coli during lag phase

    LENUS (Irish Health Repository)

    Pin, Carmen

    2009-11-16

    Abstract Background The aging process of bacteria in stationary phase is halted if cells are subcultured and enter lag phase and it is then followed by cellular division. Network science has been applied to analyse the transcriptional response, during lag phase, of bacterial cells starved previously in stationary phase for 1 day (young cells) and 16 days (old cells). Results A genome scale network was constructed for E. coli K-12 by connecting genes with operons, transcription and sigma factors, metabolic pathways and cell functional categories. Most of the transcriptional changes were detected immediately upon entering lag phase and were maintained throughout this period. The lag period was longer for older cells and the analysis of the transcriptome revealed different intracellular activity in young and old cells. The number of genes differentially expressed was smaller in old cells (186) than in young cells (467). Relatively, few genes (62) were up- or down-regulated in both cultures. Transcription of genes related to osmotolerance, acid resistance, oxidative stress and adaptation to other stresses was down-regulated in both young and old cells. Regarding carbohydrate metabolism, genes related to the citrate cycle were up-regulated in young cells while old cells up-regulated the Entner Doudoroff and gluconate pathways and down-regulated the pentose phosphate pathway. In both old and young cells, anaerobic respiration and fermentation pathways were down-regulated, but only young cells up-regulated aerobic respiration while there was no evidence of aerobic respiration in old cells. Numerous genes related to DNA maintenance and replication, translation, ribosomal biosynthesis and RNA processing as well as biosynthesis of the cell envelope and flagellum and several components of the chemotaxis signal transduction complex were up-regulated only in young cells. The genes for several transport proteins for iron compounds were up-regulated in both young and old cells

  6. Network analysis of the transcriptional pattern of young and old cells of Escherichia coli during lag phase

    Directory of Open Access Journals (Sweden)

    Hinton Jay CD

    2009-11-01

    Full Text Available Abstract Background The aging process of bacteria in stationary phase is halted if cells are subcultured and enter lag phase and it is then followed by cellular division. Network science has been applied to analyse the transcriptional response, during lag phase, of bacterial cells starved previously in stationary phase for 1 day (young cells and 16 days (old cells. Results A genome scale network was constructed for E. coli K-12 by connecting genes with operons, transcription and sigma factors, metabolic pathways and cell functional categories. Most of the transcriptional changes were detected immediately upon entering lag phase and were maintained throughout this period. The lag period was longer for older cells and the analysis of the transcriptome revealed different intracellular activity in young and old cells. The number of genes differentially expressed was smaller in old cells (186 than in young cells (467. Relatively, few genes (62 were up- or down-regulated in both cultures. Transcription of genes related to osmotolerance, acid resistance, oxidative stress and adaptation to other stresses was down-regulated in both young and old cells. Regarding carbohydrate metabolism, genes related to the citrate cycle were up-regulated in young cells while old cells up-regulated the Entner Doudoroff and gluconate pathways and down-regulated the pentose phosphate pathway. In both old and young cells, anaerobic respiration and fermentation pathways were down-regulated, but only young cells up-regulated aerobic respiration while there was no evidence of aerobic respiration in old cells. Numerous genes related to DNA maintenance and replication, translation, ribosomal biosynthesis and RNA processing as well as biosynthesis of the cell envelope and flagellum and several components of the chemotaxis signal transduction complex were up-regulated only in young cells. The genes for several transport proteins for iron compounds were up-regulated in both young

  7. Reverse engineering a mouse embryonic stem cell-specific transcriptional network reveals a new modulator of neuronal differentiation.

    Science.gov (United States)

    De Cegli, Rossella; Iacobacci, Simona; Flore, Gemma; Gambardella, Gennaro; Mao, Lei; Cutillo, Luisa; Lauria, Mario; Klose, Joachim; Illingworth, Elizabeth; Banfi, Sandro; di Bernardo, Diego

    2013-01-01

    Gene expression profiles can be used to infer previously unknown transcriptional regulatory interaction among thousands of genes, via systems biology 'reverse engineering' approaches. We 'reverse engineered' an embryonic stem (ES)-specific transcriptional network from 171 gene expression profiles, measured in ES cells, to identify master regulators of gene expression ('hubs'). We discovered that E130012A19Rik (E13), highly expressed in mouse ES cells as compared with differentiated cells, was a central 'hub' of the network. We demonstrated that E13 is a protein-coding gene implicated in regulating the commitment towards the different neuronal subtypes and glia cells. The overexpression and knock-down of E13 in ES cell lines, undergoing differentiation into neurons and glia cells, caused a strong up-regulation of the glutamatergic neurons marker Vglut2 and a strong down-regulation of the GABAergic neurons marker GAD65 and of the radial glia marker Blbp. We confirmed E13 expression in the cerebral cortex of adult mice and during development. By immuno-based affinity purification, we characterized protein partners of E13, involved in the Polycomb complex. Our results suggest a role of E13 in regulating the division between glutamatergic projection neurons and GABAergic interneurons and glia cells possibly by epigenetic-mediated transcriptional regulation.

  8. Transcriptional network underlying Caenorhabditis elegans vulval development.

    Science.gov (United States)

    Inoue, Takao; Wang, Minqin; Ririe, Ted O; Fernandes, Jolene S; Sternberg, Paul W

    2005-04-05

    The vulval development of Caenorhabditis elegans provides an opportunity to investigate genetic networks that control gene expression during organogenesis. During the fourth larval stage (L4), seven vulval cell types are produced, each of which executes a distinct gene expression program. We analyze how the expression of cell-type-specific genes is regulated. Ras and Wnt signaling pathways play major roles in generating the spatial pattern of cell types and regulate gene expression through a network of transcription factors. One transcription factor (lin-29) primarily controls the temporal expression pattern. Other transcription factors (lin-11, cog-1, and egl-38) act in combination to control cell-type-specific gene expression. The complexity of the network arises in part because of the dynamic nature of gene expression, in part because of the presence of seven cell types, and also because there are multiple regulatory paths for gene expression within each cell type.

  9. Melanoma cells revive an embryonic transcriptional network to dictate phenotypic heterogeneity.

    Science.gov (United States)

    Vandamme, Niels; Berx, Geert

    2014-01-01

    Compared to the overwhelming amount of literature describing how epithelial-to-mesenchymal transition (EMT)-inducing transcription factors orchestrate cellular plasticity in embryogenesis and epithelial cells, the functions of these factors in non-epithelial contexts, such as melanoma, are less clear. Melanoma is an aggressive tumor arising from melanocytes, endowed with unique features of cellular plasticity. The reversible phenotype-switching between differentiated and invasive phenotypes is increasingly appreciated as a mechanism accounting for heterogeneity in melanoma and is driven by oncogenic signaling and environmental cues. This phenotypic switch is coupled with an intriguing and somewhat counterintuitive signaling switch of EMT-inducing transcription factors. In contrast to carcinomas, different EMT-inducing transcription factors have antagonizing effects in melanoma. Balancing between these different EMT transcription factors is likely the key to successful metastatic spread of melanoma.

  10. The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line

    DEFF Research Database (Denmark)

    Suzuki, Harukazu; Forrest, Alistair R R; van Nimwegen, Erik

    2009-01-01

    Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites...

  11. The B-MYB transcriptional network guides cell cycle progression and fate decisions to sustain self-renewal and the identity of pluripotent stem cells.

    Directory of Open Access Journals (Sweden)

    Ming Zhan

    Full Text Available Embryonic stem cells (ESCs are pluripotent and have unlimited self-renewal capacity. Although pluripotency and differentiation have been examined extensively, the mechanisms responsible for self-renewal are poorly understood and are believed to involve an unusual cell cycle, epigenetic regulators and pluripotency-promoting transcription factors. Here we show that B-MYB, a cell cycle regulated phosphoprotein and transcription factor critical to the formation of inner cell mass, is central to the transcriptional and co-regulatory networks that sustain normal cell cycle progression and self-renewal properties of ESCs. Phenotypically, B-MYB is robustly expressed in ESCs and induced pluripotent stem cells (iPSCs, and it is present predominantly in a hypo-phosphorylated state. Knockdown of B-MYB results in functional cell cycle abnormalities that involve S, G2 and M phases, and reduced expression of critical cell cycle regulators like ccnb1 and plk1. By conducting gene expression profiling on control and B-MYB deficient cells, ChIP-chip experiments, and integrative computational analyses, we unraveled a highly complex B-MYB-mediated transcriptional network that guides ESC self-renewal. The network encompasses critical regulators of all cell cycle phases and epigenetic regulators, pluripotency transcription factors, and differentiation determinants. B-MYB along with E2F1 and c-MYC preferentially co-regulate cell cycle target genes. B-MYB also co-targets genes regulated by OCT4, SOX2 and NANOG that are significantly associated with stem cell differentiation, embryonic development, and epigenetic control. Moreover, loss of B-MYB leads to a breakdown of the transcriptional hierarchy present in ESCs. These results coupled with functional studies demonstrate that B-MYB not only controls and accelerates cell cycle progression in ESCs it contributes to fate decisions and maintenance of pluripotent stem cell identity.

  12. The B-MYB transcriptional network guides cell cycle progression and fate decisions to sustain self-renewal and the identity of pluripotent stem cells.

    Science.gov (United States)

    Zhan, Ming; Riordon, Daniel R; Yan, Bin; Tarasova, Yelena S; Bruweleit, Sarah; Tarasov, Kirill V; Li, Ronald A; Wersto, Robert P; Boheler, Kenneth R

    2012-01-01

    Embryonic stem cells (ESCs) are pluripotent and have unlimited self-renewal capacity. Although pluripotency and differentiation have been examined extensively, the mechanisms responsible for self-renewal are poorly understood and are believed to involve an unusual cell cycle, epigenetic regulators and pluripotency-promoting transcription factors. Here we show that B-MYB, a cell cycle regulated phosphoprotein and transcription factor critical to the formation of inner cell mass, is central to the transcriptional and co-regulatory networks that sustain normal cell cycle progression and self-renewal properties of ESCs. Phenotypically, B-MYB is robustly expressed in ESCs and induced pluripotent stem cells (iPSCs), and it is present predominantly in a hypo-phosphorylated state. Knockdown of B-MYB results in functional cell cycle abnormalities that involve S, G2 and M phases, and reduced expression of critical cell cycle regulators like ccnb1 and plk1. By conducting gene expression profiling on control and B-MYB deficient cells, ChIP-chip experiments, and integrative computational analyses, we unraveled a highly complex B-MYB-mediated transcriptional network that guides ESC self-renewal. The network encompasses critical regulators of all cell cycle phases and epigenetic regulators, pluripotency transcription factors, and differentiation determinants. B-MYB along with E2F1 and c-MYC preferentially co-regulate cell cycle target genes. B-MYB also co-targets genes regulated by OCT4, SOX2 and NANOG that are significantly associated with stem cell differentiation, embryonic development, and epigenetic control. Moreover, loss of B-MYB leads to a breakdown of the transcriptional hierarchy present in ESCs. These results coupled with functional studies demonstrate that B-MYB not only controls and accelerates cell cycle progression in ESCs it contributes to fate decisions and maintenance of pluripotent stem cell identity.

  13. Evidence for transcript networks composed of chimeric RNAs in human cells.

    Directory of Open Access Journals (Sweden)

    Sarah Djebali

    Full Text Available The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5' and 3' transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1 the non-random interconnections of genes involved, (2 the greater phylogenetic depth of the genes involved in many chimeric interactions, (3 the coordination of the expression of connected genes and (4 the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network.

  14. BMP signaling orchestrates a transcriptional network to control the fate of mesenchymal stem cells in mice.

    Science.gov (United States)

    Feng, Jifan; Jing, Junjun; Li, Jingyuan; Zhao, Hu; Punj, Vasu; Zhang, Tingwei; Xu, Jian; Chai, Yang

    2017-07-15

    Signaling pathways are used reiteratively in different developmental processes yet produce distinct cell fates through specific downstream transcription factors. In this study, we used tooth root development as a model with which to investigate how the BMP signaling pathway regulates transcriptional complexes to direct the fate determination of multipotent mesenchymal stem cells (MSCs). We first identified the MSC population supporting mouse molar root growth as Gli1(+) cells. Using a Gli1-driven Cre-mediated recombination system, our results provide the first in vivo evidence that BMP signaling activity is required for the odontogenic differentiation of MSCs. Specifically, we identified the transcription factors Pax9, Klf4, Satb2 and Lhx8 as being downstream of BMP signaling and expressed in a spatially restricted pattern that is potentially involved in determining distinct cellular identities within the dental mesenchyme. Finally, we found that overactivation of one key transcription factor, Klf4, which is associated with the odontogenic region, promotes odontogenic differentiation of MSCs. Collectively, our results demonstrate the functional significance of BMP signaling in regulating MSC fate during root development and shed light on how BMP signaling can achieve functional specificity in regulating diverse organ development. © 2017. Published by The Company of Biologists Ltd.

  15. Escherichia coli transcriptional regulatory network

    Directory of Open Access Journals (Sweden)

    Agustino Martinez-Antonio

    2011-06-01

    Full Text Available Escherichia coli is the most well-know bacterial model about the function of its molecular components. In this review are presented several structural and functional aspects of their transcriptional regulatory network constituted by transcription factors and target genes. The network discussed here represent to 1531 genes and 3421 regulatory interactions. This network shows a power-law distribution with a few global regulators and most of genes poorly connected. 176 of genes in the network correspond to transcription factors, which form a sub-network of seven hierarchical layers where global regulators tend to be set in superior layers while local regulators are located in the lower ones. There is a small set of proteins know as nucleoid-associated proteins, which are in a high cellular concentrations and reshape the nucleoid structure to influence the running of global transcriptional programs, to this mode of regulation is named analog regulation. Specific signal effectors assist the activity of most of transcription factors in E. coli. These effectors switch and tune the activity of transcription factors. To this type of regulation, depending of environmental signals is named the digital-precise-regulation. The integration of regulatory programs have place in the promoter region of transcription units where it is common to observe co-regulation among global and local TFs as well as of TFs sensing exogenous and endogenous conditions. The mechanistic logic to understand the harmonious operation of regulatory programs in the network should consider the globalism of TFs, their signal perceived, coregulation, genome position, and cellular concentration. Finally, duplicated TFs and their horizontal transfer influence the evolvability of members of the network. The most duplicated and transferred TFs are located in the network periphery.

  16. The network of cytokines, receptors and transcription factors governing the development of dendritic cell subsets

    OpenAIRE

    Sathe, Priyanka; Wu, Li

    2011-01-01

    The pathways leading to the development of different dendritic cell (DC) subsets have long been unclear. In recent years, a number of precursors on the route to DC development, both under steady state and inflammatory conditions, have been described, and the nature of these pathways is becoming clearer. In addition, the development of various knockout mouse models and an in vitro system modelling DC development have revealed the role of numerous cytokines and transcription factors that influe...

  17. Cell-type-selective induction of c-jun by TAF4b directs ovarian-specific transcription networks.

    Science.gov (United States)

    Geles, Kenneth G; Freiman, Richard N; Liu, Wei-Li; Zheng, Shuang; Voronina, Ekaterina; Tjian, Robert

    2006-02-21

    Cell-type-selective expression of the TFIID subunit TAF(II)105 (renamed TAF4b) in the ovary is essential for proper follicle development. Although a multitude of signaling pathways required for folliculogenesis have been identified, downstream transcriptional integrators of these signals remain largely unknown. Here, we show that TAF4b controls the granulosa-cell-specific expression of the proto-oncogene c-jun, and together they regulate transcription of ovary-selective promoters. Instead of using cell-type-specific activators, our findings suggest that the coactivator TAF4b regulates the expression of tissue-specific genes, at least in part, through the cell-type-specific induction of c-jun, a ubiquitous activator. Importantly, the loss of TAF4b in ovarian granulosa cells disrupts cellular morphologies and interactions during follicle growth that likely contribute to the infertility observed in TAF4b-null female mice. These data highlight a mechanism for potentiating tissue-selective functions of the basal transcription machinery and reveal intricate networks of gene expression that orchestrate ovarian-specific functions and cell morphology.

  18. Transcriptional network in ovarian cancer cell line SKOV3 treated with Pinellia pedatisecta Schott extract.

    Science.gov (United States)

    Zhou, Li; Xu, Teng; Zhang, Ying; Zhu, Mei; Zhu, Wen; Wang, Ziqiang; Gu, Hangzhi; Wang, Hanchu; Li, Peizhen; Ying, Jun; Yang, Lei; Ren, Ping; Li, Jinsong; Xu, Zuyuan; Ni, Liyan; Bao, Qiyu; Chen, Jindong

    2016-07-01

    Ovarian cancer is the most lethal disease among the malignant tumors of female reproductive organs. Few successful therapeutic options exist for patients with ovarian cancer. The common therapeutic methods are surgical operation, chemotherapy, radiotherapy, and combination of these treatments. In recent years, studies have indicated that Pinellia pedatisecta Schott (PPS), a traditional Chinese medicine, could inhibit tumor growth. In this study, we demonstrated that PPS extract could induce apoptosis in SKOV3 cells in a dose- and time-dependent manner. We further conducted transcriptome sequencing on PPS extract-treated SKOV3 cells along with controls, and identified 1,754 transcripts whose expression differs at least 3-fold over the controls. These differentially expressed transcripts include the apoptosis-related genes such as the caspase family members, and were significantly enriched in steroid biosynthesis in the KEGG pathway database compared with the transcriptome background. Most of the differentially expressed transcripts from this pathway were upregulated in PPS extract-treated cell line, indicating that PPS extract-induced apoptosis was accompanied by increased steroid biosynthesis (e.g. zymosterol). These results suggest that PPS extract could be a new cytostatic therapeutic agent for ovarian cancer.

  19. A Druggable TCF4- and BRD4-Dependent Transcriptional Network Sustains Malignancy in Blastic Plasmacytoid Dendritic Cell Neoplasm.

    Science.gov (United States)

    Ceribelli, Michele; Hou, Zhiying Esther; Kelly, Priscilla N; Huang, Da Wei; Wright, George; Ganapathi, Karthik; Evbuomwan, Moses O; Pittaluga, Stefania; Shaffer, Arthur L; Marcucci, Guido; Forman, Stephen J; Xiao, Wenming; Guha, Rajarshi; Zhang, Xiaohu; Ferrer, Marc; Chaperot, Laurence; Plumas, Joel; Jaffe, Elaine S; Thomas, Craig J; Reizis, Boris; Staudt, Louis M

    2016-11-14

    Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is an aggressive and largely incurable hematologic malignancy originating from plasmacytoid dendritic cells (pDCs). Using RNAi screening, we identified the E-box transcription factor TCF4 as a master regulator of the BPDCN oncogenic program. TCF4 served as a faithful diagnostic marker of BPDCN, and its downregulation caused the loss of the BPDCN-specific gene expression program and apoptosis. High-throughput drug screening revealed that bromodomain and extra-terminal domain inhibitors (BETis) induced BPDCN apoptosis, which was attributable to disruption of a BPDCN-specific transcriptional network controlled by TCF4-dependent super-enhancers. BETis retarded the growth of BPDCN xenografts, supporting their clinical evaluation in this recalcitrant malignancy.

  20. MINCR is a MYC-induced lncRNA able to modulate MYC's transcriptional network in Burkitt lymphoma cells.

    Science.gov (United States)

    Doose, Gero; Haake, Andrea; Bernhart, Stephan H; López, Cristina; Duggimpudi, Sujitha; Wojciech, Franziska; Bergmann, Anke K; Borkhardt, Arndt; Burkhardt, Birgit; Claviez, Alexander; Dimitrova, Lora; Haas, Siegfried; Hoell, Jessica I; Hummel, Michael; Karsch, Dennis; Klapper, Wolfram; Kleo, Karsten; Kretzmer, Helene; Kreuz, Markus; Küppers, Ralf; Lawerenz, Chris; Lenze, Dido; Loeffler, Markus; Mantovani-Löffler, Luisa; Möller, Peter; Ott, German; Richter, Julia; Rohde, Marius; Rosenstiel, Philip; Rosenwald, Andreas; Schilhabel, Markus; Schneider, Markus; Scholz, Ingrid; Stilgenbauer, Stephan; Stunnenberg, Hendrik G; Szczepanowski, Monika; Trümper, Lorenz; Weniger, Marc A; Hoffmann, Steve; Siebert, Reiner; Iaccarino, Ingram

    2015-09-22

    Despite the established role of the transcription factor MYC in cancer, little is known about the impact of a new class of transcriptional regulators, the long noncoding RNAs (lncRNAs), on MYC ability to influence the cellular transcriptome. Here, we have intersected RNA-sequencing data from two MYC-inducible cell lines and a cohort of 91 B-cell lymphomas with or without genetic variants resulting in MYC overexpression. We identified 13 lncRNAs differentially expressed in IG-MYC-positive Burkitt lymphoma and regulated in the same direction by MYC in the model cell lines. Among them, we focused on a lncRNA that we named MYC-induced long noncoding RNA (MINCR), showing a strong correlation with MYC expression in MYC-positive lymphomas. To understand its cellular role, we performed RNAi and found that MINCR knockdown is associated with an impairment in cell cycle progression. Differential gene expression analysis after RNAi showed a significant enrichment of cell cycle genes among the genes down-regulated after MINCR knockdown. Interestingly, these genes are enriched in MYC binding sites in their promoters, suggesting that MINCR acts as a modulator of the MYC transcriptional program. Accordingly, MINCR knockdown was associated with a reduction in MYC binding to the promoters of selected cell cycle genes. Finally, we show that down-regulation of Aurora kinases A and B and chromatin licensing and DNA replication factor 1 may explain the reduction in cellular proliferation observed on MINCR knockdown. We, therefore, suggest that MINCR is a newly identified player in the MYC transcriptional network able to control the expression of cell cycle genes.

  1. Measurement and modeling of transcriptional noise in the cell cycle regulatory network.

    Science.gov (United States)

    Ball, David A; Adames, Neil R; Reischmann, Nadine; Barik, Debashis; Franck, Christopher T; Tyson, John J; Peccoud, Jean

    2013-10-01

    Fifty years of genetic and molecular experiments have revealed a wealth of molecular interactions involved in the control of cell division. In light of the complexity of this control system, mathematical modeling has proved useful in analyzing biochemical hypotheses that can be tested experimentally. Stochastic modeling has been especially useful in understanding the intrinsic variability of cell cycle events, but stochastic modeling has been hampered by a lack of reliable data on the absolute numbers of mRNA molecules per cell for cell cycle control genes. To fill this void, we used fluorescence in situ hybridization (FISH) to collect single molecule mRNA data for 16 cell cycle regulators in budding yeast, Saccharomyces cerevisiae. From statistical distributions of single-cell mRNA counts, we are able to extract the periodicity, timing, and magnitude of transcript abundance during the cell cycle. We used these parameters to improve a stochastic model of the cell cycle to better reflect the variability of molecular and phenotypic data on cell cycle progression in budding yeast.

  2. A novel SALL4/OCT4 transcriptional feedback network for pluripotency of embryonic stem cells.

    Directory of Open Access Journals (Sweden)

    Jianchang Yang

    Full Text Available BACKGROUND: SALL4 is a member of the SALL gene family that encodes a group of putative developmental transcription factors. Murine Sall4 plays a critical role in maintaining embryonic stem cell (ES cell pluripotency and self-renewal. We have shown that Sall4 activates Oct4 and is a master regulator in murine ES cells. Other SALL gene members, especially Sall1 and Sall3 are expressed in both murine and human ES cells, and deletions of these two genes in mice lead to perinatal death due to developmental defects. To date, little is known about the molecular mechanisms controlling the regulation of expressions of SALL4 or other SALL gene family members. METHODOLOGY/PRINCIPAL FINDINGS: This report describes a novel SALL4/OCT4 regulator feedback loop in ES cells in balancing the proper expression dosage of SALL4 and OCT4 for the maintenance of ESC stem cell properties. While we have observed that a positive feedback relationship is present between SALL4 and OCT4, the strong self-repression of SALL4 seems to be the "break" for this loop. In addition, we have shown that SALL4 can repress the promoters of other SALL family members, such as SALL1 and SALL3, which competes with the activation of these two genes by OCT4. CONCLUSIONS/SIGNIFICANCE: Our findings, when taken together, indicate that SALL4 is a master regulator that controls its own expression and the expression of OCT4. SALL4 and OCT4 work antagonistically to balance the expressions of other SALL gene family members. This novel SALL4/OCT4 transcription regulation feedback loop should provide more insight into the mechanism of governing the "stemness" of ES cells.

  3. Subventricular zone microglia transcriptional networks.

    Science.gov (United States)

    Starossom, Sarah C; Imitola, Jaime; Wang, Yue; Cao, Li; Khoury, Samia J

    2011-07-01

    Microglia play an important role in inflammatory diseases of the central nervous system. There is evidence of microglial diversity with distinct phenotypes exhibiting either neuroprotection and repair or neurotoxicity. However the precise molecular mechanisms underlying this diversity are still unknown. Using a model of experimental autoimmune encephalomyelitis (EAE) we performed transcriptional profiling of isolated subventricular zone microglia from the acute and chronic disease phases of EAE. We found that microglia exhibit disease phase specific gene expression signatures, that correspond to unique gene ontology functions and genomic networks. Our data demonstrate for the first time, distinct transcriptional networks of microglia activation in vivo, that suggests a role as mediators of injury or repair.

  4. Complex Coordination of Cell Plasticity by a PGC-1α-controlled Transcriptional Network in Skeletal Muscle.

    Science.gov (United States)

    Kupr, Barbara; Handschin, Christoph

    2015-01-01

    Skeletal muscle cells exhibit an enormous plastic capacity in order to adapt to external stimuli. Even though our overall understanding of the molecular mechanisms that underlie phenotypic changes in skeletal muscle cells remains poor, several factors involved in the regulation and coordination of relevant transcriptional programs have been identified in recent years. For example, the peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) is a central regulatory nexus in the adaptation of muscle to endurance training. Intriguingly, PGC-1α integrates numerous signaling pathways and translates their activity into various transcriptional programs. This selectivity is in part controlled by differential expression of PGC-1α variants and post-translational modifications of the PGC-1α protein. PGC-1α-controlled activation of transcriptional networks subsequently enables a spatio-temporal specification and hence allows a complex coordination of changes in metabolic and contractile properties, protein synthesis and degradation rates and other features of trained muscle. In this review, we discuss recent advances in our understanding of PGC-1α-regulated skeletal muscle cell plasticity in health and disease.

  5. Complex coordination of cell plasticity by a PGC-1α-controlled transcriptional network in skeletal muscle

    Directory of Open Access Journals (Sweden)

    Barbara eKupr

    2015-11-01

    Full Text Available Skeletal muscle cells exhibit an enormous plastic capacity in order to adapt to external stimuli. Even though our overall understanding of the molecular mechanisms that underlie phenotypic changes in skeletal muscle cells remains poor, several factors involved in the regulation and coordination of relevant transcriptional programs have been identified in recent years. For example, the peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α is a central regulatory nexus in the adaptation of muscle to endurance training. Intriguingly, PGC-1α integrates numerous signaling pathways and translates their activity into various transcriptional programs. This selectivity is in part controlled by differential expression of PGC-1α variants and post-translational modifications of the PGC-1α protein. PGC-1α-controlled activation of transcriptional networks subsequently enables a spatio-temporal specification and hence allows a complex coordination of changes in metabolic and contractile properties, protein synthesis and degradation rates and other features of trained muscle. In this review, we discuss recent advances in our understanding of PGC-1α-regulated skeletal muscle cell plasticity in health and disease.

  6. Ascl1 as a novel player in the Ptf1a transcriptional network for GABAergic cell specification in the retina.

    Science.gov (United States)

    Mazurier, Nicolas; Parain, Karine; Parlier, Damien; Pretto, Silvia; Hamdache, Johanna; Vernier, Philippe; Locker, Morgane; Bellefroid, Eric; Perron, Muriel

    2014-01-01

    In contrast with the wealth of data involving bHLH and homeodomain transcription factors in retinal cell type determination, the molecular bases underlying neurotransmitter subtype specification is far less understood. Using both gain and loss of function analyses in Xenopus, we investigated the putative implication of the bHLH factor Ascl1 in this process. We found that in addition to its previously characterized proneural function, Ascl1 also contributes to the specification of the GABAergic phenotype. We showed that it is necessary for retinal GABAergic cell genesis and sufficient in overexpression experiments to bias a subset of retinal precursor cells towards a GABAergic fate. We also analysed the relationships between Ascl1 and a set of other bHLH factors using an in vivo ectopic neurogenic assay. We demonstrated that Ascl1 has unique features as a GABAergic inducer and is epistatic over factors endowed with glutamatergic potentialities such as Neurog2, NeuroD1 or Atoh7. This functional specificity is conferred by the basic DNA binding domain of Ascl1 and involves a specific genetic network, distinct from that underlying its previously demonstrated effects on catecholaminergic differentiation. Our data show that GABAergic inducing activity of Ascl1 requires the direct transcriptional regulation of Ptf1a, providing therefore a new piece of the network governing neurotransmitter subtype specification during retinogenesis.

  7. Ascl1 as a novel player in the Ptf1a transcriptional network for GABAergic cell specification in the retina.

    Directory of Open Access Journals (Sweden)

    Nicolas Mazurier

    Full Text Available In contrast with the wealth of data involving bHLH and homeodomain transcription factors in retinal cell type determination, the molecular bases underlying neurotransmitter subtype specification is far less understood. Using both gain and loss of function analyses in Xenopus, we investigated the putative implication of the bHLH factor Ascl1 in this process. We found that in addition to its previously characterized proneural function, Ascl1 also contributes to the specification of the GABAergic phenotype. We showed that it is necessary for retinal GABAergic cell genesis and sufficient in overexpression experiments to bias a subset of retinal precursor cells towards a GABAergic fate. We also analysed the relationships between Ascl1 and a set of other bHLH factors using an in vivo ectopic neurogenic assay. We demonstrated that Ascl1 has unique features as a GABAergic inducer and is epistatic over factors endowed with glutamatergic potentialities such as Neurog2, NeuroD1 or Atoh7. This functional specificity is conferred by the basic DNA binding domain of Ascl1 and involves a specific genetic network, distinct from that underlying its previously demonstrated effects on catecholaminergic differentiation. Our data show that GABAergic inducing activity of Ascl1 requires the direct transcriptional regulation of Ptf1a, providing therefore a new piece of the network governing neurotransmitter subtype specification during retinogenesis.

  8. Examination of transcriptional networks reveals an important role for TCFAP2C, SMARCA4, and EOMES in trophoblast stem cell maintenance.

    Science.gov (United States)

    Kidder, Benjamin L; Palmer, Stephen

    2010-04-01

    Trophoblast stem cells (TS cells), derived from the trophectoderm (TE) of blastocysts, require transcription factors (TFs) and external signals (FGF4, INHBA/NODAL/TGFB1) for self-renewal. While many reports have focused on TF networks that regulate embryonic stem cell (ES cell) self-renewal and pluripotency, little is know about TF networks that regulate self-renewal in TS cells. To further understand transcriptional networks in TS cells, we used chromatin immunoprecipitation with DNA microarray hybridization (ChIP-chip) analysis to investigate targets of the TFs-TCFAP2C, EOMES, ETS2, and GATA3-and a chromatin remodeling factor, SMARCA4. We then evaluated the transcriptional states of target genes using transcriptome analysis and genome-wide analysis of histone H3 acetylation (AcH3). Our results describe previously unknown transcriptional networks in TS cells, including TF occupancy of genes involved in ES cell self-renewal and pluripotency, co-occupancy of TCFAP2C, SMARCA4, and EOMES at a significant number of genes, and transcriptional regulatory circuitry within the five factors. Moreover, RNAi depletion of Tcfap2c, Smarca4, and Eomes transcripts resulted in a loss of normal colony morphology and down-regulation of TS cell-specific genes, suggesting an important role for TCFAP2C, SMARCA4, and EOMES in TS cell self-renewal. Through genome-wide mapping and global expression analysis of five TF target genes, our data provide a comprehensive analysis of transcriptional networks that regulate TS cell self-renewal.

  9. Transcriptional coexpression network reveals the involvement of varying stem cell features with different dysregulations in different gastric cancer subtypes.

    Science.gov (United States)

    Kalamohan, Kalaivani; Periasamy, Jayaprakash; Bhaskar Rao, Divya; Barnabas, Georgina D; Ponnaiyan, Srigayatri; Ganesan, Kumaresan

    2014-10-01

    Despite the advancements in the cancer therapeutics, gastric cancer ranks as the second most common cancers with high global mortality rate. Integrative functional genomic investigation is a powerful approach to understand the major dysregulations and to identify the potential targets toward the development of targeted therapeutics for various cancers. Intestinal and diffuse type gastric tumors remain the major subtypes and the molecular determinants and drivers of these distinct subtypes remain unidentified. In this investigation, by exploring the network of gene coexpression association in gastric tumors, mRNA expressions of 20,318 genes across 200 gastric tumors were categorized into 21 modules. The genes and the hub genes of the modules show gastric cancer subtype specific expression. The expression patterns of the modules were correlated with intestinal and diffuse subtypes as well as with the differentiation status of gastric tumors. Among these, G1 module has been identified as a major driving force of diffuse type gastric tumors with the features of (i) enriched mesenchymal, mesenchymal stem cell like, and mesenchymal derived multiple lineages, (ii) elevated OCT1 mediated transcription, (iii) involvement of Notch activation, and (iv) reduced polycomb mediated epigenetic repression. G13 module has been identified as key factor in intestinal type gastric tumors and found to have the characteristic features of (i) involvement of embryonic stem cell like properties, (ii) Wnt, MYC and E2F mediated transcription programs, and (iii) involvement of polycomb mediated repression. Thus the differential transcription programs, differential epigenetic regulation and varying stem cell features involved in two major subtypes of gastric cancer were delineated by exploring the gene coexpression network. The identified subtype specific dysregulations could be optimally employed in developing subtype specific therapeutic targeting strategies for gastric cancer.

  10. Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors

    DEFF Research Database (Denmark)

    Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

    2015-01-01

    Transcriptional regulation is the most committed type of regulation in living cells where transcription factors (TFs) control the expression of their target genes and TF expression is controlled by other TFs forming complex transcriptional regulatory networks that can be highly interconnected. Here...... we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network...... as a measure of the organization and interconnectivity of the network. We find that the number of driver nodes n(D) needed to control the whole network is 64% of the TFs in the E. coli transcriptional regulatory network in contrast to only 17% for the yeast network, 4% for the mouse network and 8...

  11. Integrating phosphorylation network with transcriptional network reveals novel functional relationships.

    Directory of Open Access Journals (Sweden)

    Lin Wang

    Full Text Available Phosphorylation and transcriptional regulation events are critical for cells to transmit and respond to signals. In spite of its importance, systems-level strategies that couple these two networks have yet to be presented. Here we introduce a novel approach that integrates the physical and functional aspects of phosphorylation network together with the transcription network in S.cerevisiae, and demonstrate that different network motifs are involved in these networks, which should be considered in interpreting and integrating large scale datasets. Based on this understanding, we introduce a HeRS score (hetero-regulatory similarity score to systematically characterize the functional relevance of kinase/phosphatase involvement with transcription factor, and present an algorithm that predicts hetero-regulatory modules. When extended to signaling network, this approach confirmed the structure and cross talk of MAPK pathways, inferred a novel functional transcription factor Sok2 in high osmolarity glycerol pathway, and explained the mechanism of reduced mating efficiency upon Fus3 deletion. This strategy is applicable to other organisms as large-scale datasets become available, providing a means to identify the functional relationships between kinases/phosphatases and transcription factors.

  12. Transcriptional networks in leaf senescence.

    Science.gov (United States)

    Schippers, Jos H M

    2015-10-01

    Plant senescence is a natural phenomenon known for the appearance of beautiful autumn colors and the ripening of cereals in the field. Senescence is a controlled process that plants utilize to remobilize nutrients from source leaves to developing tissues. While during the past decades, molecular components underlying the onset of senescence have been intensively studied, knowledge remains scarce on the age-dependent mechanisms that control the onset of senescence. Recent advances have uncovered transcriptional networks regulating the competence to senesce. Here, gene regulatory networks acting as internal timing mechanisms for the onset of senescence are highlighted, illustrating that early and late leaf developmental phases are highly connected.

  13. Transcriptional networks in plant immunity.

    Science.gov (United States)

    Tsuda, Kenichi; Somssich, Imre E

    2015-05-01

    Next to numerous abiotic stresses, plants are constantly exposed to a variety of pathogens within their environment. Thus, their ability to survive and prosper during the course of evolution was strongly dependent on adapting efficient strategies to perceive and to respond to such potential threats. It is therefore not surprising that modern plants have a highly sophisticated immune repertoire consisting of diverse signal perception and intracellular signaling pathways. This signaling network is intricate and deeply interconnected, probably reflecting the diverse lifestyles and infection strategies used by the multitude of invading phytopathogens. Moreover it allows signal communication between developmental and defense programs thereby ensuring that plant growth and fitness are not significantly retarded. How plants integrate and prioritize the incoming signals and how this information is transduced to enable appropriate immune responses is currently a major research area. An important finding has been that pathogen-triggered cellular responses involve massive transcriptional reprogramming within the host. Additional key observations emerging from such studies are that transcription factors (TFs) are often sites of signal convergence and that signal-regulated TFs act in concert with other context-specific TFs and transcriptional co-regulators to establish sensory transcription regulatory networks required for plant immunity.

  14. Characterization of transcription factor networks involved in umbilical cord blood CD34+ stem cells-derived erythropoiesis.

    Directory of Open Access Journals (Sweden)

    Biaoru Li

    Full Text Available Fetal stem cells isolated from umbilical cord blood (UCB possess a great capacity for proliferation and differentiation and serve as a valuable model system to study gene regulation. Expanded knowledge of the molecular control of hemoglobin synthesis will provide a basis for rational design of therapies for β-hemoglobinopathies. Transcriptome data are available for erythroid progenitors derived from adult stem cells, however studies to define molecular mechanisms controlling globin gene regulation during fetal erythropoiesis are limited. Here, we utilize UCB-CD34+ stem cells induced to undergo erythroid differentiation to characterize the transcriptome and transcription factor networks (TFNs associated with the γ/β-globin switch during fetal erythropoiesis. UCB-CD34+ stem cells grown in the one-phase liquid culture system displayed a higher proliferative capacity than adult CD34+ stem cells. The γ/β-globin switch was observed after day 42 during fetal erythropoiesis in contrast to adult progenitors where the switch occurred around day 21. To gain insights into transcription factors involved in globin gene regulation, microarray analysis was performed on RNA isolated from UCB-CD34+ cell-derived erythroid progenitors harvested on day 21, 42, 49 and 56 using the HumanHT-12 Expression BeadChip. After data normalization, Gene Set Enrichment Analysis identified transcription factors (TFs with significant changes in expression during the γ/β-globin switch. Forty-five TFs were silenced by day 56 (Profile-1 and 30 TFs were activated by day 56 (Profile-2. Both GSEA datasets were analyzed using the MIMI Cytoscape platform, which discovered TFNs centered on KLF4 and GATA2 (Profile-1 and KLF1 and GATA1 for Profile-2 genes. Subsequent shRNA studies in KU812 leukemia cells and human erythroid progenitors generated from UCB-CD34+ cells supported a negative role of MAFB in γ-globin regulation. The characteristics of erythroblasts derived from UCB-CD34

  15. Loss of variation of state detected in soybean metabolic and human myelomonocytic leukaemia cell transcriptional networks under external stimuli.

    Science.gov (United States)

    Sakata, Katsumi; Saito, Toshiyuki; Ohyanagi, Hajime; Okumura, Jun; Ishige, Kentaro; Suzuki, Harukazu; Nakamura, Takuji; Komatsu, Setsuko

    2016-10-24

    Soybean (Glycine max) is sensitive to flooding stress, and flood damage at the seedling stage is a barrier to growth. We constructed two mathematical models of the soybean metabolic network, a control model and a flooded model, from metabolic profiles in soybean plants. We simulated the metabolic profiles with perturbations before and after the flooding stimulus using the two models. We measured the variation of state that the system could maintain from a state-space description of the simulated profiles. The results showed a loss of variation of state during the flooding response in the soybean plants. Loss of variation of state was also observed in a human myelomonocytic leukaemia cell transcriptional network in response to a phorbol-ester stimulus. Thus, we detected a loss of variation of state under external stimuli in two biological systems, regardless of the regulation and stimulus types. Our results suggest that a loss of robustness may occur concurrently with the loss of variation of state in biological systems. We describe the possible applications of the quantity of variation of state in plant genetic engineering and cell biology. Finally, we present a hypothetical "external stimulus-induced information loss" model of biological systems.

  16. Loss of variation of state detected in soybean metabolic and human myelomonocytic leukaemia cell transcriptional networks under external stimuli

    KAUST Repository

    Sakata, Katsumi

    2016-10-24

    Soybean (Glycine max) is sensitive to flooding stress, and flood damage at the seedling stage is a barrier to growth. We constructed two mathematical models of the soybean metabolic network, a control model and a flooded model, from metabolic profiles in soybean plants. We simulated the metabolic profiles with perturbations before and after the flooding stimulus using the two models. We measured the variation of state that the system could maintain from a state–space description of the simulated profiles. The results showed a loss of variation of state during the flooding response in the soybean plants. Loss of variation of state was also observed in a human myelomonocytic leukaemia cell transcriptional network in response to a phorbol-ester stimulus. Thus, we detected a loss of variation of state under external stimuli in two biological systems, regardless of the regulation and stimulus types. Our results suggest that a loss of robustness may occur concurrently with the loss of variation of state in biological systems. We describe the possible applications of the quantity of variation of state in plant genetic engineering and cell biology. Finally, we present a hypothetical “external stimulus-induced information loss” model of biological systems.

  17. Transcription Factor Networks derived from Breast Cancer Stem Cells control the immune response in the Basal subtype

    DEFF Research Database (Denmark)

    da Silveira, W A; Palma, P V B; Sicchieri, R D

    2017-01-01

    from putative bCSC and reverse engineering of transcription control networks, we identified two networks associated with this phenotype. One controlled by SNAI2, TWIST1, BNC2, PRRX1 and TBX5 drives a mesenchymal or CSC-like phenotype. The second network is controlled by the SCML4, ZNF831, SP140...... and IKZF3 transcription factors which correspond to immune response modulators. Immune response network expression is correlated with pathological response to chemotherapy, and in the Basal subtype is related to better recurrence-free survival. In patient-derived xenografts, the expression...... of these networks in patient tumours is predictive of engraftment success. Our findings point out a potential molecular mechanism underlying the balance between immune surveillance and EMT activation in breast cancer. This molecular mechanism may be useful to the development of new target therapies....

  18. Networks in Cell Biology

    Science.gov (United States)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  19. Transcriptional networks in epithelial-mesenchymal transition.

    Directory of Open Access Journals (Sweden)

    Christo Venkov

    Full Text Available Epithelial-mesenchymal transition (EMT changes polarized epithelial cells into migratory phenotypes associated with loss of cell-cell adhesion molecules and cytoskeletal rearrangements. This form of plasticity is seen in mesodermal development, fibroblast formation, and cancer metastasis.Here we identify prominent transcriptional networks active during three time points of this transitional process, as epithelial cells become fibroblasts. DNA microarray in cultured epithelia undergoing EMT, validated in vivo, were used to detect various patterns of gene expression. In particular, the promoter sequences of differentially expressed genes and their transcription factors were analyzed to identify potential binding sites and partners. The four most frequent cis-regulatory elements (CREs in up-regulated genes were SRY, FTS-1, Evi-1, and GC-Box, and RNA inhibition of the four transcription factors, Atf2, Klf10, Sox11, and SP1, most frequently binding these CREs, establish their importance in the initiation and propagation of EMT. Oligonucleotides that block the most frequent CREs restrain EMT at early and intermediate stages through apoptosis of the cells.Our results identify new transcriptional interactions with high frequency CREs that modulate the stability of cellular plasticity, and may serve as targets for modulating these transitional states in fibroblasts.

  20. Evolutionary dynamics of prokaryotic transcriptional regulatory networks.

    Science.gov (United States)

    Madan Babu, M; Teichmann, Sarah A; Aravind, L

    2006-04-28

    The structure of complex transcriptional regulatory networks has been studied extensively in certain model organisms. However, the evolutionary dynamics of these networks across organisms, which would reveal important principles of adaptive regulatory changes, are poorly understood. We use the known transcriptional regulatory network of Escherichia coli to analyse the conservation patterns of this network across 175 prokaryotic genomes, and predict components of the regulatory networks for these organisms. We observe that transcription factors are typically less conserved than their target genes and evolve independently of them, with different organisms evolving distinct repertoires of transcription factors responding to specific signals. We show that prokaryotic transcriptional regulatory networks have evolved principally through widespread tinkering of transcriptional interactions at the local level by embedding orthologous genes in different types of regulatory motifs. Different transcription factors have emerged independently as dominant regulatory hubs in various organisms, suggesting that they have convergently acquired similar network structures approximating a scale-free topology. We note that organisms with similar lifestyles across a wide phylogenetic range tend to conserve equivalent interactions and network motifs. Thus, organism-specific optimal network designs appear to have evolved due to selection for specific transcription factors and transcriptional interactions, allowing responses to prevalent environmental stimuli. The methods for biological network analysis introduced here can be applied generally to study other networks, and these predictions can be used to guide specific experiments.

  1. Mapping mammalian cell-type-specific transcriptional regulatory networks using KD-CAGE and ChIP-seq data in the TC-YIK cell line.

    Directory of Open Access Journals (Sweden)

    Marina eLizio

    2015-11-01

    Full Text Available Mammals are composed of hundreds of different cell types with specialized functions. Each of these cellular phenotypes are controlled by different combinations of transcription factors. Using a human non islet cell insulinoma cell line (TC-YIK which expresses insulin and the majority of known pancreatic beta cell specific genes as an example, we describe a general approach to identify key cell-type-specific transcription factors (TFs and their direct and indirect targets. By ranking all human TFs by their level of enriched expression in TC-YIK relative to a broad collection of samples (FANTOM5, we confirmed known key regulators of pancreatic function and development. Systematic siRNA mediated perturbation of these TFs followed by qRT-PCR revealed their interconnections with NEUROD1 at the top of the regulation hierarchy and its depletion drastically reducing insulin levels. For 15 of the TF knock-downs (KD, we then used Cap Analysis of Gene Expression (CAGE to identify thousands of their targets genome-wide (KD-CAGE. The data confirm NEUROD1 as a key positive regulator in the transcriptional regulatory network (TRN, and ISL1 and PROX1 as antagonists. As a complimentary approach we used ChIP-seq on four of these factors to identify NEUROD1, LMX1A, PAX6 and RFX6 binding sites in the human genome. Examining the overlap between genes perturbed in the KD-CAGE experiments and genes with a ChIP-seq peak within 1kb of their promoter, we identified direct transcriptional targets of these TFs. Integration of KD-CAGE and ChIP-seq data shows that both NEUROD1 and LMX1A work as the main transcriptional activators. In the core TRN (i.e. TF-TF only, NEUROD1 directly transcriptionally activates the pancreatic TFs HSF4, INSM1, MLXIPL, MYT1, NKX6-3, ONECUT2, PAX4, PROX1, RFX6, ST18, DACH1 and SHOX2, while LMX1A directly transcriptionally activates DACH1, SHOX2, PAX6 and PDX1. Analysis of these complementary datasets suggests the need for caution in interpreting

  2. Mapping Mammalian Cell-type-specific Transcriptional Regulatory Networks Using KD-CAGE and ChIP-seq Data in the TC-YIK Cell Line.

    Science.gov (United States)

    Lizio, Marina; Ishizu, Yuri; Itoh, Masayoshi; Lassmann, Timo; Hasegawa, Akira; Kubosaki, Atsutaka; Severin, Jessica; Kawaji, Hideya; Nakamura, Yukio; Suzuki, Harukazu; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R

    2015-01-01

    Mammals are composed of hundreds of different cell types with specialized functions. Each of these cellular phenotypes are controlled by different combinations of transcription factors. Using a human non islet cell insulinoma cell line (TC-YIK) which expresses insulin and the majority of known pancreatic beta cell specific genes as an example, we describe a general approach to identify key cell-type-specific transcription factors (TFs) and their direct and indirect targets. By ranking all human TFs by their level of enriched expression in TC-YIK relative to a broad collection of samples (FANTOM5), we confirmed known key regulators of pancreatic function and development. Systematic siRNA mediated perturbation of these TFs followed by qRT-PCR revealed their interconnections with NEUROD1 at the top of the regulation hierarchy and its depletion drastically reducing insulin levels. For 15 of the TF knock-downs (KD), we then used Cap Analysis of Gene Expression (CAGE) to identify thousands of their targets genome-wide (KD-CAGE). The data confirm NEUROD1 as a key positive regulator in the transcriptional regulatory network (TRN), and ISL1, and PROX1 as antagonists. As a complimentary approach we used ChIP-seq on four of these factors to identify NEUROD1, LMX1A, PAX6, and RFX6 binding sites in the human genome. Examining the overlap between genes perturbed in the KD-CAGE experiments and genes with a ChIP-seq peak within 50 kb of their promoter, we identified direct transcriptional targets of these TFs. Integration of KD-CAGE and ChIP-seq data shows that both NEUROD1 and LMX1A work as the main transcriptional activators. In the core TRN (i.e., TF-TF only), NEUROD1 directly transcriptionally activates the pancreatic TFs HSF4, INSM1, MLXIPL, MYT1, NKX6-3, ONECUT2, PAX4, PROX1, RFX6, ST18, DACH1, and SHOX2, while LMX1A directly transcriptionally activates DACH1, SHOX2, PAX6, and PDX1. Analysis of these complementary datasets suggests the need for caution in interpreting Ch

  3. Mathematical model of a telomerase transcriptional regulatory network developed by cell-based screening: analysis of inhibitor effects and telomerase expression mechanisms.

    Directory of Open Access Journals (Sweden)

    Alan E Bilsland

    2014-02-01

    Full Text Available Cancer cells depend on transcription of telomerase reverse transcriptase (TERT. Many transcription factors affect TERT, though regulation occurs in context of a broader network. Network effects on telomerase regulation have not been investigated, though deeper understanding of TERT transcription requires a systems view. However, control over individual interactions in complex networks is not easily achievable. Mathematical modelling provides an attractive approach for analysis of complex systems and some models may prove useful in systems pharmacology approaches to drug discovery. In this report, we used transfection screening to test interactions among 14 TERT regulatory transcription factors and their respective promoters in ovarian cancer cells. The results were used to generate a network model of TERT transcription and to implement a dynamic Boolean model whose steady states were analysed. Modelled effects of signal transduction inhibitors successfully predicted TERT repression by Src-family inhibitor SU6656 and lack of repression by ERK inhibitor FR180204, results confirmed by RT-QPCR analysis of endogenous TERT expression in treated cells. Modelled effects of GSK3 inhibitor 6-bromoindirubin-3'-oxime (BIO predicted unstable TERT repression dependent on noise and expression of JUN, corresponding with observations from a previous study. MYC expression is critical in TERT activation in the model, consistent with its well known function in endogenous TERT regulation. Loss of MYC caused complete TERT suppression in our model, substantially rescued only by co-suppression of AR. Interestingly expression was easily rescued under modelled Ets-factor gain of function, as occurs in TERT promoter mutation. RNAi targeting AR, JUN, MXD1, SP3, or TP53, showed that AR suppression does rescue endogenous TERT expression following MYC knockdown in these cells and SP3 or TP53 siRNA also cause partial recovery. The model therefore successfully predicted several

  4. The Transcription Factor Network in Embryonic Stem Cells: The virtue of promiscuity?

    NARCIS (Netherlands)

    D.L.C. van den Berg (Debbie)

    2010-01-01

    textabstractEmbryonic stem (ES) cells are derived from the inner cell mass of blastocyst stage embryos and when cultured in vitro can self-renew indefinitely while retaining the capacity to differentiate into derivatives of the three germ layers. These key properties are regulated by a core transcri

  5. Sequencing the transcriptional network of androgen receptor in prostate cancer.

    Science.gov (United States)

    Chng, Kern Rei; Cheung, Edwin

    2013-11-01

    The progression of prostate cancer is largely dependent on the activity of the androgen receptor (AR), which in turn, correlates with the net output of the AR transcriptional regulatory network. A detailed and thorough understanding of the AR transcriptional regulatory network is therefore critical in the strategic manipulation of AR activity for the targeted eradication of prostate cancer cells. In this mini-review, we highlight some of the novel and unexpected mechanistic and functional insights of the AR transcriptional network derived from recent targeted sequencing (ChIP-Seq) studies of AR and its coregulatory factors in prostate cancer cells.

  6. Transcription Dynamics in Living Cells.

    Science.gov (United States)

    Lenstra, Tineke L; Rodriguez, Joseph; Chen, Huimin; Larson, Daniel R

    2016-07-01

    The transcription cycle can be roughly divided into three stages: initiation, elongation, and termination. Understanding the molecular events that regulate all these stages requires a dynamic view of the underlying processes. The development of techniques to visualize and quantify transcription in single living cells has been essential in revealing the transcription kinetics. They have revealed that (a) transcription is heterogeneous between cells and (b) transcription can be discontinuous within a cell. In this review, we discuss the progress in our quantitative understanding of transcription dynamics in living cells, focusing on all parts of the transcription cycle. We present the techniques allowing for single-cell transcription measurements, review evidence from different organisms, and discuss how these experiments have broadened our mechanistic understanding of transcription regulation.

  7. SCL/TAL1-mediated transcriptional network enhances megakaryocytic specification of human embryonic stem cells.

    Science.gov (United States)

    Toscano, Miguel G; Navarro-Montero, Oscar; Ayllon, Veronica; Ramos-Mejia, Veronica; Guerrero-Carreno, Xiomara; Bueno, Clara; Romero, Tamara; Lamolda, Mar; Cobo, Marien; Martin, Francisco; Menendez, Pablo; Real, Pedro J

    2015-01-01

    Human embryonic stem cells (hESCs) are a unique in vitro model for studying human developmental biology and represent a potential source for cell replacement strategies. Platelets can be generated from cord blood progenitors and hESCs; however, the molecular mechanisms and determinants controlling the in vitro megakaryocytic specification of hESCs remain elusive. We have recently shown that stem cell leukemia (SCL) overexpression accelerates the emergence of hemato-endothelial progenitors from hESCs and promotes their subsequent differentiation into blood cells with higher clonogenic potential. Given that SCL participates in megakaryocytic commitment, we hypothesized that it may potentiate megakaryopoiesis from hESCs. We show that ectopic SCL expression enhances the emergence of megakaryocytic precursors, mature megakaryocytes (MKs), and platelets in vitro. SCL-overexpressing MKs and platelets respond to different activating stimuli similar to their control counterparts. Gene expression profiling of megakaryocytic precursors shows that SCL overexpression renders a megakaryopoietic molecular signature. Connectivity Map analysis reveals that trichostatin A (TSA) and suberoylanilide hydroxamic acid (SAHA), both histone deacetylase (HDAC) inhibitors, functionally mimic SCL-induced effects. Finally, we confirm that both TSA and SAHA treatment promote the emergence of CD34(+) progenitors, whereas valproic acid, another HDAC inhibitor, potentiates MK and platelet production. We demonstrate that SCL and HDAC inhibitors are megakaryopoiesis regulators in hESCs.

  8. Controllability analysis of transcriptional regulatory networks reveals circular control patterns among transcription factors.

    Science.gov (United States)

    Österlund, Tobias; Bordel, Sergio; Nielsen, Jens

    2015-05-01

    Transcriptional regulation is the most committed type of regulation in living cells where transcription factors (TFs) control the expression of their target genes and TF expression is controlled by other TFs forming complex transcriptional regulatory networks that can be highly interconnected. Here we analyze the topology and organization of nine transcriptional regulatory networks for E. coli, yeast, mouse and human, and we evaluate how the structure of these networks influences two of their key properties, namely controllability and stability. We calculate the controllability for each network as a measure of the organization and interconnectivity of the network. We find that the number of driver nodes nD needed to control the whole network is 64% of the TFs in the E. coli transcriptional regulatory network in contrast to only 17% for the yeast network, 4% for the mouse network and 8% for the human network. The high controllability (low number of drivers needed to control the system) in yeast, mouse and human is due to the presence of internal loops in their regulatory networks where the TFs regulate each other in a circular fashion. We refer to these internal loops as circular control motifs (CCM). The E. coli transcriptional regulatory network, which does not have any CCMs, shows a hierarchical structure of the transcriptional regulatory network in contrast to the eukaryal networks. The presence of CCMs also has influence on the stability of these networks, as the presence of cycles can be associated with potential unstable steady-states where even small changes in binding affinities can cause dramatic rearrangements of the state of the network.

  9. Evolutionary tinkering with conserved components of a transcriptional regulatory network.

    OpenAIRE

    Hugo Lavoie; Hervé Hogues; Jaideep Mallick; Adnane Sellam; André Nantel; Malcolm Whiteway

    2010-01-01

    Gene expression variation between species is a major contributor to phenotypic diversity, yet the underlying flexibility of transcriptional regulatory networks remains largely unexplored. Transcription of the ribosomal regulon is a critical task for all cells; in S. cerevisiae the transcription factors Rap1, Fhl1, Ifh1, and Hmo1 form a multi-subunit complex that controls ribosomal gene expression, while in C. albicans this regulation is under the control of Tbf1 and Cbf1. Here, we analyzed, u...

  10. Transcriptional networks controlling adipocyte differentiation

    DEFF Research Database (Denmark)

    Siersbæk, R; Mandrup, Susanne

    2011-01-01

    Adipocyte differentiation is regulated by a complex cascade of signals that drive the transcriptional reprogramming of the fibroblastic precursors. Genome-wide analyses of chromatin accessibility and binding of adipogenic transcription factors make it possible to generate "snapshots" of the trans...

  11. Transcription Adaptation during In Vitro Adipogenesis and Osteogenesis of Porcine Mesenchymal Stem Cells: Dynamics of Pathways, Biological Processes, Up-Stream Regulators, and Gene Networks.

    Science.gov (United States)

    Bionaz, Massimo; Monaco, Elisa; Wheeler, Matthew B

    2015-01-01

    The importance of mesenchymal stem cells (MSC) for bone regeneration is growing. Among MSC the bone marrow-derived stem cells (BMSC) are considered the gold standard in tissue engineering and regenerative medicine; however, the adipose-derived stem cells (ASC) have very similar properties and some advantages to be considered a good alternative to BMSC. The molecular mechanisms driving adipogenesis are relatively well-known but mechanisms driving osteogenesis are poorly known, particularly in pig. In the present study we have used transcriptome analysis to unravel pathways and biological functions driving in vitro adipogenesis and osteogenesis in BMSC and ASC. The analysis was performed using the novel Dynamic Impact Approach and functional enrichment analysis. In addition, a k-mean cluster analysis in association with enrichment analysis, networks reconstruction, and transcription factors overlapping analysis were performed in order to uncover the coordination of biological functions underlining differentiations. Analysis indicated a larger and more coordinated transcriptomic adaptation during adipogenesis compared to osteogenesis, with a larger induction of metabolism, particularly lipid synthesis (mostly triglycerides), and a larger use of amino acids for synthesis of feed-forward adipogenic compounds, larger cell signaling, lower cell-to-cell interactions, particularly for the cytoskeleton organization and cell junctions, and lower cell proliferation. The coordination of adipogenesis was mostly driven by Peroxisome Proliferator-activated Receptors together with other known adipogenic transcription factors. Only a few pathways and functions were more induced during osteogenesis compared to adipogenesis and some were more inhibited during osteogenesis, such as cholesterol and protein synthesis. Up-stream transcription factor analysis indicated activation of several lipid-related transcription regulators (e.g., PPARs and CEBPα) during adipogenesis but osteogenesis

  12. Identification of host transcriptional networks showing concentration-dependent regulation by HPV16 E6 and E7 proteins in basal cervical squamous epithelial cells.

    Science.gov (United States)

    Smith, Stephen P; Scarpini, Cinzia G; Groves, Ian J; Odle, Richard I; Coleman, Nicholas

    2016-07-26

    Development of cervical squamous cell carcinoma requires increased expression of the major high-risk human-papillomavirus (HPV) oncogenes E6 and E7 in basal cervical epithelial cells. We used a systems biology approach to identify host transcriptional networks in such cells and study the concentration-dependent changes produced by HPV16-E6 and -E7 oncoproteins. We investigated sample sets derived from the W12 model of cervical neoplastic progression, for which high quality phenotype/genotype data were available. We defined a gene co-expression matrix containing a small number of highly-connected hub nodes that controlled large numbers of downstream genes (regulons), indicating the scale-free nature of host gene co-expression in W12. We identified a small number of 'master regulators' for which downstream effector genes were significantly associated with protein levels of HPV16 E6 (n = 7) or HPV16 E7 (n = 5). We validated our data by depleting E6/E7 in relevant cells and by functional analysis of selected genes in vitro. We conclude that the network of transcriptional interactions in HPV16-infected basal-type cervical epithelium is regulated in a concentration-dependent manner by E6/E7, via a limited number of central master-regulators. These effects are likely to be significant in cervical carcinogenesis, where there is competitive selection of cells with elevated expression of virus oncoproteins.

  13. Combinatorial Regulation in Yeast Transcription Networks

    Science.gov (United States)

    Li, Hao

    2006-03-01

    Yeast has evolved a complex network to regulate its transcriptional program in response to changes in environment. It is quite common that in response to an external stimulus, several transcription factors will be activated and they work in combinations to control different subsets of genes in the genome. We are interested in how the promoters of genes are designed to integrate signals from multiple transcription factors and what are the functional and evolutionary constraints. To answer how, we have developed a number of computational algorithms to systematically map the binding sites and target genes of transcription factors using sequence and gene expression data. To analyze the functional constraints, we have employed mechanistic models to study the dynamic behavior of genes regulated by multiple factors. We have also developed methods to trace the evolution of transcriptional networks via comparative analysis of multiple species.

  14. How to build transcriptional network models of mammalian pattern formation.

    Directory of Open Access Journals (Sweden)

    Chrissa Kioussi

    Full Text Available BACKGROUND: Genetic regulatory networks of sequence specific transcription factors underlie pattern formation in multicellular organisms. Deciphering and representing the mammalian networks is a central problem in development, neurobiology, and regenerative medicine. Transcriptional networks specify intermingled embryonic cell populations during pattern formation in the vertebrate neural tube. Each embryonic population gives rise to a distinct type of adult neuron. The homeodomain transcription factor Lbx1 is expressed in five such populations and loss of Lbx1 leads to distinct respecifications in each of the five populations. METHODOLOGY/PRINCIPAL FINDINGS: We have purified normal and respecified pools of these five populations from embryos bearing one or two copies of the null Lbx1(GFP allele, respectively. Microarrays were used to show that expression levels of 8% of all transcription factor genes were altered in the respecified pool. These transcription factor genes constitute 20-30% of the active nodes of the transcriptional network that governs neural tube patterning. Half of the 141 regulated nodes were located in the top 150 clusters of ultraconserved non-coding regions. Generally, Lbx1 repressed genes that have expression patterns outside of the Lbx1-expressing domain and activated genes that have expression patterns inside the Lbx1-expressing domain. CONCLUSIONS/SIGNIFICANCE: Constraining epistasis analysis of Lbx1 to only those cells that normally express Lbx1 allowed unprecedented sensitivity in identifying Lbx1 network interactions and allowed the interactions to be assigned to a specific set of cell populations. We call this method ANCEA, or active node constrained epistasis analysis, and think that it will be generally useful in discovering and assigning network interactions to specific populations. We discuss how ANCEA, coupled with population partitioning analysis, can greatly facilitate the systematic dissection of

  15. Deciphering modular and dynamic behaviors of transcriptional networks.

    Science.gov (United States)

    Zhan, Ming

    2007-01-01

    The coordinated and dynamic modulation or interaction of genes or proteins acts as an important mechanism used by a cell in functional regulation. Recent studies have shown that many transcriptional networks exhibit a scale-free topology and hierarchical modular architecture. It has also been shown that transcriptional networks or pathways are dynamic and behave only in certain ways and controlled manners in response to disease development, changing cellular conditions, and different environmental factors. Moreover, evolutionarily conserved and divergent transcriptional modules underline fundamental and species-specific molecular mechanisms controlling disease development or cellular phenotypes. Various computational algorithms have been developed to explore transcriptional networks and modules from gene expression data. In silico studies have also been made to mimic the dynamic behavior of regulatory networks, analyzing how disease or cellular phenotypes arise from the connectivity or networks of genes and their products. Here, we review the recent development in computational biology research on deciphering modular and dynamic behaviors of transcriptional networks, highlighting important findings. We also demonstrate how these computational algorithms can be applied in systems biology studies as on disease, stem cells, and drug discovery.

  16. Reconstruction of transcriptional network from microarray data using combined mutual information and network-assisted regression.

    Science.gov (United States)

    Wang, X-D; Qi, Y-X; Jiang, Z-L

    2011-03-01

    Many methods had been developed on inferring transcriptional network from gene expression. However, it is still necessary to design new method that discloses more detailed and exact network information. Using network-assisted regression, the authors combined the averaged three-way mutual information (AMI3) and non-linear ordinary differential equation (ODE) model to infer the transcriptional network, and to obtain both the topological structure and the regulatory dynamics. Synthetic and experimental data were used to evaluate the performance of the above approach. In comparison with the previous methods based on mutual information, AMI3 obtained higher precision with the same sensitivity. To describe the regulatory dynamics between transcription factors and target genes, network-assisted regression and regression without network, respectively, were applied in the steady-state and time series microarray data. The results revealed that comparing with regression without network, network-assisted regression increased the precision, but decreased the fitting goodness. Then, the authors reconstructed the transcriptional network of Escherichia coli and simulated the regulatory dynamics of genes. Furthermore, the authors' approach identified potential transcription factors regulating yeast cell cycle. In conclusion, network-assisted regression, combined AMI3 and ODE model, was a more precisely to infer the topological structure and the regulatory dynamics of transcriptional network from microarray data. [Includes supplementary material].

  17. Transcription regulatory networks analysis using CAGE

    KAUST Repository

    Tegnér, Jesper N.

    2009-10-01

    Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

  18. SOX2 gene regulates the transcriptional network of oncogenes and affects tumorigenesis of human lung cancer cells.

    Directory of Open Access Journals (Sweden)

    Si Chen

    Full Text Available Recent studies demonstrated that cancer stem cells (CSCs have higher tumorigenesis properties than those of differentiated cancer cells and that transcriptional factor-SOX2 plays a vital role in maintaining the unique properties of CSCs; however, the function and underlying mechanism of SOX2 in carcinogenesis of lung cancer are still elusive. This study applied immunohistochemistry to analyze the expression of SOX2 in human lung tissues of normal individuals as well as patients with adenocarcinoma, squamous cell carcinoma, and large cell and small cell carcinoma and demonstrated specific overexpression of SOX2 in all types of lung cancer tissues. This finding supports the notion that SOX2 contributes to the tumorigenesis of lung cancer cells and can be used as a diagnostic probe. In addition, obviously higher expression of oncogenes c-MYC, WNT1, WNT2, and NOTCH1 was detected in side population (SP cells than in non-side population (NSP cells of human lung adenocarcinoma cell line-A549, revealing a possible mechanism for the tenacious tumorigenic potential of CSCs. To further elucidate the function of SOX2 in tumorigenesis of cancer cells, A549 cells were established with expression of luciferase and doxycycline-inducible shRNA targeting SOX2. We found silencing of SOX2 gene reduces the tumorigenic property of A549 cells with attenuated expression of c-MYC, WNT1, WNT2, and NOTCH1 in xenografted NOD/SCID mice. By using the RNA-Seq method, an additional 246 target cancer genes of SOX2 were revealed. These results present evidence that SOX2 may regulate the expression of oncogenes in CSCs to promote the development of human lung cancer.

  19. SOX2 gene regulates the transcriptional network of oncogenes and affects tumorigenesis of human lung cancer cells.

    Science.gov (United States)

    Chen, Si; Xu, Yingxi; Chen, Yanan; Li, Xuefei; Mou, Wenjun; Wang, Lina; Liu, Yanhua; Reisfeld, Ralph A; Xiang, Rong; Lv, Dan; Li, Na

    2012-01-01

    Recent studies demonstrated that cancer stem cells (CSCs) have higher tumorigenesis properties than those of differentiated cancer cells and that transcriptional factor-SOX2 plays a vital role in maintaining the unique properties of CSCs; however, the function and underlying mechanism of SOX2 in carcinogenesis of lung cancer are still elusive. This study applied immunohistochemistry to analyze the expression of SOX2 in human lung tissues of normal individuals as well as patients with adenocarcinoma, squamous cell carcinoma, and large cell and small cell carcinoma and demonstrated specific overexpression of SOX2 in all types of lung cancer tissues. This finding supports the notion that SOX2 contributes to the tumorigenesis of lung cancer cells and can be used as a diagnostic probe. In addition, obviously higher expression of oncogenes c-MYC, WNT1, WNT2, and NOTCH1 was detected in side population (SP) cells than in non-side population (NSP) cells of human lung adenocarcinoma cell line-A549, revealing a possible mechanism for the tenacious tumorigenic potential of CSCs. To further elucidate the function of SOX2 in tumorigenesis of cancer cells, A549 cells were established with expression of luciferase and doxycycline-inducible shRNA targeting SOX2. We found silencing of SOX2 gene reduces the tumorigenic property of A549 cells with attenuated expression of c-MYC, WNT1, WNT2, and NOTCH1 in xenografted NOD/SCID mice. By using the RNA-Seq method, an additional 246 target cancer genes of SOX2 were revealed. These results present evidence that SOX2 may regulate the expression of oncogenes in CSCs to promote the development of human lung cancer.

  20. Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network.

    Science.gov (United States)

    Hosseinpour, Batool; Bakhtiarizadeh, Mohammad Reza; Khosravi, Pegah; Ebrahimie, Esmaeil

    2013-12-01

    Self-proliferation and differentiation into distinct cell types have been made stem cell as a promising target for regenerative medicine. Several key genes can regulate self-renewal and pluripotency of embryonic stem cells (hESCs). They work together and build a transcriptional hierarchy. Coexpression and coregulation of genes control by common regulatory elements on the promoter regions. Consequently, distinct organization and combination of transcription factor binding sites (TFBSs modules) on promoter regions, in view of order and distance, lead to a common specific expression pattern within a set of genes. To gain insights into transcriptional regulation of hESCs, we selected promoter regions of eleven common expressed hESC genes including SOX2, LIN28, STAT3, NANOG, LEFTB, TDGF1, POU5F1, FOXD3, TERF1, REX1 and GDF3 to predict activating regulatory modules on promoters and discover key corresponding transcription factors. Then, promoter regions in human genome were explored for modules and 328 genes containing the same modules were detected. Using microarray data, we verified that 102 of 328 genes commonly upregulate in hESCs. Also, using output data of DNA-protein interaction assays, we found that 42 of all predicted genes are targets of SOX2, NANOG and POU5F1. Additionally, a protein interaction network of hESC genes was constructed based on biological processes, and interestingly, 126 downregulated genes along with upregulated ones identified by promoter analysis were predicted in the network. Based on the results, we suggest that the identified genes, coregulating with common hESC genes, represent a novel approach for gene discovery based on whole genome promoter analysis irrespective of gene expression. Altogether, promoter profiling can be used to expand hESC transcriptional regulatory circuitry by analysis of shared functional sequences between genes. This approach provides a clear image on underlying regulatory mechanism of gene expression profile and

  1. Dynamic network of transcription and pathway crosstalk to reveal molecular mechanism of MGd-treated human lung cancer cells.

    Directory of Open Access Journals (Sweden)

    Liyan Shao

    Full Text Available Recent research has revealed various molecular markers in lung cancer. However, the organizational principles underlying their genetic regulatory networks still await investigation. Here we performed Network Component Analysis (NCA and Pathway Crosstalk Analysis (PCA to construct a regulatory network in human lung cancer (A549 cells which were treated with 50 uM motexafin gadolinium (MGd, a metal cation-containing chemotherapeutic drug for 4, 12, and 24 hours. We identified a set of key TFs, known target genes for these TFs, and signaling pathways involved in regulatory networks. Our work showed that putative interactions between these TFs (such as ESR1/Sp1, E2F1/Sp1, c-MYC-ESR, Smad3/c-Myc, and NFKB1/RELA, between TFs and their target genes (such as BMP41/Est1, TSC2/Myc, APE1/Sp1/p53, RARA/HOXA1, and SP1/USF2, and between signaling pathways (such as PPAR signaling pathway and Adipocytokines signaling pathway. These results will provide insights into the regulatory mechanism of MGd-treated human lung cancer cells.

  2. Characterizing disease states from topological properties of transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Kluger Harriet M

    2006-05-01

    Full Text Available Abstract Background High throughput gene expression experiments yield large amounts of data that can augment our understanding of disease processes, in addition to classifying samples. Here we present new paradigms of data Separation based on construction of transcriptional regulatory networks for normal and abnormal cells using sequence predictions, literature based data and gene expression studies. We analyzed expression datasets from a number of diseased and normal cells, including different types of acute leukemia, and breast cancer with variable clinical outcome. Results We constructed sample-specific regulatory networks to identify links between transcription factors (TFs and regulated genes that differentiate between healthy and diseased states. This approach carries the advantage of identifying key transcription factor-gene pairs with differential activity between healthy and diseased states rather than merely using gene expression profiles, thus alluding to processes that may be involved in gene deregulation. We then generalized this approach by studying simultaneous changes in functionality of multiple regulatory links pointing to a regulated gene or emanating from one TF (or changes in gene centrality defined by its in-degree or out-degree measures, respectively. We found that samples can often be separated based on these measures of gene centrality more robustly than using individual links. We examined distributions of distances (the number of links needed to traverse the path between each pair of genes in the transcriptional networks for gene subsets whose collective expression profiles could best separate each dataset into predefined groups. We found that genes that optimally classify samples are concentrated in neighborhoods in the gene regulatory networks. This suggests that genes that are deregulated in diseased states exhibit a remarkable degree of connectivity. Conclusion Transcription factor-regulated gene links and

  3. Analysis of FOXO transcriptional networks

    NARCIS (Netherlands)

    van der Vos, K.E.

    2010-01-01

    The PI3K-PKB-FOXO signalling module plays a pivotal role in a wide variety of cellular processes, including proliferation, survival, differentiation and metabolism. Inappropriate activation of this network is frequently observed in human cancer and causes uncontrolled proliferation and survival. In

  4. Transcriptional networks leading to symbiotic nodule organogenesis.

    Science.gov (United States)

    Soyano, Takashi; Hayashi, Makoto

    2014-08-01

    The symbiosis with nitrogen-fixing bacteria leading to root nodules is a relatively recent evolutionary innovation and limited to a distinct order of land plants. It has long been a mystery how plants have invented this complex trait. However, recent advances in molecular genetics of model legumes has elucidated genes involved in the development of root nodules, providing insights into this process. Here we discuss how the de novo assembly of transcriptional networks may account for the predisposition to nodulate. Transcriptional networks and modes of gene regulation from the arbuscular mycorrhizal symbiosis, nitrate responses and aspects of lateral root development have likely all contributed to the emergence and development of root nodules.

  5. Decoding the Pluripotency Network: The Emergence of New Transcription Factors

    Directory of Open Access Journals (Sweden)

    Kai Chuen Lee

    2013-12-01

    Full Text Available Since the successful isolation of mouse and human embryonic stem cells (ESCs in the past decades, massive investigations have been conducted to dissect the pluripotency network that governs the ability of these cells to differentiate into all cell types. Beside the core Oct4-Sox2-Nanog circuitry, accumulating regulators, including transcription factors, epigenetic modifiers, microRNA and signaling molecules have also been found to play important roles in preserving pluripotency. Among the various regulations that orchestrate the cellular pluripotency program, transcriptional regulation is situated in the central position and appears to be dominant over other regulatory controls. In this review, we would like to summarize the recent advancements in the accumulating findings of new transcription factors that play a critical role in controlling both pluripotency network and ESC identity.

  6. Transcriptional master regulator analysis in breast cancer genetic networks.

    Science.gov (United States)

    Tovar, Hugo; García-Herrera, Rodrigo; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2015-12-01

    Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology.

  7. Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements

    Directory of Open Access Journals (Sweden)

    Sara J.C. Gosline

    2016-01-01

    Full Text Available MicroRNAs (miRNAs regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq and CLIP (crosslinking followed by immunoprecipitation sequencing (CLIP-seq, we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.

  8. Elucidating MicroRNA Regulatory Networks Using Transcriptional, Post-transcriptional, and Histone Modification Measurements.

    Science.gov (United States)

    Gosline, Sara J C; Gurtan, Allan M; JnBaptiste, Courtney K; Bosson, Andrew; Milani, Pamela; Dalin, Simona; Matthews, Bryan J; Yap, Yoon S; Sharp, Phillip A; Fraenkel, Ernest

    2016-01-12

    MicroRNAs (miRNAs) regulate diverse biological processes by repressing mRNAs, but their modest effects on direct targets, together with their participation in larger regulatory networks, make it challenging to delineate miRNA-mediated effects. Here, we describe an approach to characterizing miRNA-regulatory networks by systematically profiling transcriptional, post-transcriptional and epigenetic activity in a pair of isogenic murine fibroblast cell lines with and without Dicer expression. By RNA sequencing (RNA-seq) and CLIP (crosslinking followed by immunoprecipitation) sequencing (CLIP-seq), we found that most of the changes induced by global miRNA loss occur at the level of transcription. We then introduced a network modeling approach that integrated these data with epigenetic data to identify specific miRNA-regulated transcription factors that explain the impact of miRNA perturbation on gene expression. In total, we demonstrate that combining multiple genome-wide datasets spanning diverse regulatory modes enables accurate delineation of the downstream miRNA-regulated transcriptional network and establishes a model for studying similar networks in other systems.

  9. Random Boolean network models and the yeast transcriptional network

    Science.gov (United States)

    Kauffman, Stuart; Peterson, Carsten; Samuelsson, Björn; Troein, Carl

    2003-12-01

    The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.

  10. Transcription Adaptation during In Vitro Adipogenesis and Osteogenesis of Porcine Mesenchymal Stem Cells: Dynamics of Pathways, Biological Processes, Up-Stream Regulators, and Gene Networks.

    Directory of Open Access Journals (Sweden)

    Massimo Bionaz

    Full Text Available The importance of mesenchymal stem cells (MSC for bone regeneration is growing. Among MSC the bone marrow-derived stem cells (BMSC are considered the gold standard in tissue engineering and regenerative medicine; however, the adipose-derived stem cells (ASC have very similar properties and some advantages to be considered a good alternative to BMSC. The molecular mechanisms driving adipogenesis are relatively well-known but mechanisms driving osteogenesis are poorly known, particularly in pig. In the present study we have used transcriptome analysis to unravel pathways and biological functions driving in vitro adipogenesis and osteogenesis in BMSC and ASC. The analysis was performed using the novel Dynamic Impact Approach and functional enrichment analysis. In addition, a k-mean cluster analysis in association with enrichment analysis, networks reconstruction, and transcription factors overlapping analysis were performed in order to uncover the coordination of biological functions underlining differentiations. Analysis indicated a larger and more coordinated transcriptomic adaptation during adipogenesis compared to osteogenesis, with a larger induction of metabolism, particularly lipid synthesis (mostly triglycerides, and a larger use of amino acids for synthesis of feed-forward adipogenic compounds, larger cell signaling, lower cell-to-cell interactions, particularly for the cytoskeleton organization and cell junctions, and lower cell proliferation. The coordination of adipogenesis was mostly driven by Peroxisome Proliferator-activated Receptors together with other known adipogenic transcription factors. Only a few pathways and functions were more induced during osteogenesis compared to adipogenesis and some were more inhibited during osteogenesis, such as cholesterol and protein synthesis. Up-stream transcription factor analysis indicated activation of several lipid-related transcription regulators (e.g., PPARs and CEBPα during adipogenesis

  11. Gene transcriptional networks integrate microenvironmental signals in human breast cancer.

    Science.gov (United States)

    Xu, Ren; Mao, Jian-Hua

    2011-04-01

    A significant amount of evidence shows that microenvironmental signals generated from extracellular matrix (ECM) molecules, soluble factors, and cell-cell adhesion complexes cooperate at the extra- and intracellular level. This synergetic action of microenvironmental cues is crucial for normal mammary gland development and breast malignancy. To explore how the microenvironmental genes coordinate in human breast cancer at the genome level, we have performed gene co-expression network analysis in three independent microarray datasets and identified two microenvironment networks in human breast cancer tissues. Network I represents crosstalk and cooperation of ECM microenvironment and soluble factors during breast malignancy. The correlated expression of cytokines, chemokines, and cell adhesion proteins in Network II implicates the coordinated action of these molecules in modulating the immune response in breast cancer tissues. These results suggest that microenvironmental cues are integrated with gene transcriptional networks to promote breast cancer development.

  12. Dynamics of transcription-translation networks

    Science.gov (United States)

    Hudson, D.; Edwards, R.

    2016-09-01

    A theory for qualitative models of gene regulatory networks has been developed over several decades, generally considering transcription factors to regulate directly the expression of other transcription factors, without any intermediate variables. Here we explore a class of models that explicitly includes both transcription and translation, keeping track of both mRNA and protein concentrations. We mainly deal with transcription regulation functions that are steep sigmoids or step functions, as is often done in protein-only models, though translation is governed by a linear term. We extend many aspects of the protein-only theory to this new context, including properties of fixed points, description of trajectories by mappings between switching points, qualitative analysis via a state-transition diagram, and a result on periodic orbits for negative feedback loops. We find that while singular behaviour in switching domains is largely avoided, non-uniqueness of solutions can still occur in the step-function limit.

  13. Resetting the transcription factor network reverses terminal chronic hepatic failure.

    Science.gov (United States)

    Nishikawa, Taichiro; Bell, Aaron; Brooks, Jenna M; Setoyama, Kentaro; Melis, Marta; Han, Bing; Fukumitsu, Ken; Handa, Kan; Tian, Jianmin; Kaestner, Klaus H; Vodovotz, Yoram; Locker, Joseph; Soto-Gutierrez, Alejandro; Fox, Ira J

    2015-04-01

    The cause of organ failure is enigmatic for many degenerative diseases, including end-stage liver disease. Here, using a CCl4-induced rat model of irreversible and fatal hepatic failure, which also exhibits terminal changes in the extracellular matrix, we demonstrated that chronic injury stably reprograms the critical balance of transcription factors and that diseased and dedifferentiated cells can be returned to normal function by re-expression of critical transcription factors, a process similar to the type of reprogramming that induces somatic cells to become pluripotent or to change their cell lineage. Forced re-expression of the transcription factor HNF4α induced expression of the other hepatocyte-expressed transcription factors; restored functionality in terminally diseased hepatocytes isolated from CCl4-treated rats; and rapidly reversed fatal liver failure in CCl4-treated animals by restoring diseased hepatocytes rather than replacing them with new hepatocytes or stem cells. Together, the results of our study indicate that disruption of the transcription factor network and cellular dedifferentiation likely mediate terminal liver failure and suggest reinstatement of this network has therapeutic potential for correcting organ failure without cell replacement.

  14. HES6 drives a critical AR transcriptional programme to induce castration-resistant prostate cancer through activation of an E2F1-mediated cell cycle network

    Science.gov (United States)

    Ramos-Montoya, Antonio; Lamb, Alastair D; Russell, Roslin; Carroll, Thomas; Jurmeister, Sarah; Galeano-Dalmau, Nuria; Massie, Charlie E; Boren, Joan; Bon, Helene; Theodorou, Vasiliki; Vias, Maria; Shaw, Greg L; Sharma, Naomi L; Ross-Adams, Helen; Scott, Helen E; Vowler, Sarah L; Howat, William J; Warren, Anne Y; Wooster, Richard F; Mills, Ian G; Neal, David E

    2014-01-01

    Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies. PMID:24737870

  15. HES6 drives a critical AR transcriptional programme to induce castration-resistant prostate cancer through activation of an E2F1-mediated cell cycle network.

    Science.gov (United States)

    Ramos-Montoya, Antonio; Lamb, Alastair D; Russell, Roslin; Carroll, Thomas; Jurmeister, Sarah; Galeano-Dalmau, Nuria; Massie, Charlie E; Boren, Joan; Bon, Helene; Theodorou, Vasiliki; Vias, Maria; Shaw, Greg L; Sharma, Naomi L; Ross-Adams, Helen; Scott, Helen E; Vowler, Sarah L; Howat, William J; Warren, Anne Y; Wooster, Richard F; Mills, Ian G; Neal, David E

    2014-05-01

    Castrate-resistant prostate cancer (CRPC) is poorly characterized and heterogeneous and while the androgen receptor (AR) is of singular importance, other factors such as c-Myc and the E2F family also play a role in later stage disease. HES6 is a transcription co-factor associated with stem cell characteristics in neural tissue. Here we show that HES6 is up-regulated in aggressive human prostate cancer and drives castration-resistant tumour growth in the absence of ligand binding by enhancing the transcriptional activity of the AR, which is preferentially directed to a regulatory network enriched for transcription factors such as E2F1. In the clinical setting, we have uncovered a HES6-associated signature that predicts poor outcome in prostate cancer, which can be pharmacologically targeted by inhibition of PLK1 with restoration of sensitivity to castration. We have therefore shown for the first time the critical role of HES6 in the development of CRPC and identified its potential in patient-specific therapeutic strategies.

  16. Heat shock transcription factor 1 is activated as a consequence of lymphocyte activation and regulates a major proteostasis network in T cells critical for cell division during stress.

    Science.gov (United States)

    Gandhapudi, Siva K; Murapa, Patience; Threlkeld, Zachary D; Ward, Martin; Sarge, Kevin D; Snow, Charles; Woodward, Jerold G

    2013-10-15

    Heat shock transcription factor 1 (HSF1) is a major transcriptional regulator of the heat shock response in eukaryotic cells. HSF1 is evoked in response to a variety of cellular stressors, including elevated temperatures, oxidative stress, and other proteotoxic stressors. Previously, we demonstrated that HSF1 is activated in naive T cells at fever range temperatures (39.5°C) and is critical for in vitro T cell proliferation at fever temperatures. In this study, we demonstrated that murine HSF1 became activated to the DNA-binding form and transactivated a large number of genes in lymphoid cells strictly as a consequence of receptor activation in the absence of apparent cellular stress. Microarray analysis comparing HSF1(+/+) and HSF1(-/-) gene expression in T cells activated at 37°C revealed a diverse set of 323 genes significantly regulated by HSF1 in nonstressed T cells. In vivo proliferation studies revealed a significant impairment of HSF1(-/-) T cell expansion under conditions mimicking a robust immune response (staphylococcal enterotoxin B-induced T cell activation). This proliferation defect due to loss of HSF1 is observed even under nonfebrile temperatures. HSF1(-/-) T cells activated at fever temperatures show a dramatic reduction in cyclin E and cyclin A proteins during the cell cycle, although the transcription of these genes was modestly affected. Finally, B cell and hematopoietic stem cell proliferation from HSF1(-/-) mice, but not HSF1(+/+) mice, were also attenuated under stressful conditions, indicating that HSF1 is critical for the cell cycle progression of lymphoid cells activated under stressful conditions.

  17. Aberrant transcriptional networks in step-wise neurogenesis of paroxysmal kinesigenic dyskinesia-induced pluripotent stem cells.

    Science.gov (United States)

    Li, Chun; Ma, Yu; Zhang, Kunshan; Gu, Junjie; Tang, Fan; Chen, Shengdi; Cao, Li; Li, Siguang; Jin, Ying

    2016-08-16

    Paroxysmal kinesigenic dyskinesia (PKD) is an episodic movement disorder with autosomal-dominant inheritance and marked variability in clinical manifestations.Proline-rich transmembrane protein 2 (PRRT2) has been identified as a causative gene of PKD, but the molecular mechanism underlying the pathogenesis of PKD still remains a mystery. The phenotypes and transcriptional patterns of the PKD disease need further clarification. Here, we report the generation and neural differentiation of iPSC lines from two familial PKD patients with c.487C>T (p. Gln163X) and c.573dupT (p. Gly192Trpfs*8) PRRT2 mutations, respectively. Notably, an extremely lower efficiency in neural conversion from PKD-iPSCs than control-iPSCs is observed by a step-wise neural differentiation method of dual inhibition of SMAD signaling. Moreover, we show the high expression level of PRRT2 throughout the human brain and the expression pattern of PRRT2 in other human tissues for the first time. To gain molecular insight into the development of the disease, we conduct global gene expression profiling of PKD cells at four different stages of neural induction and identify altered gene expression patterns, which peculiarly reflect dysregulated neural transcriptome signatures and a differentiation tendency to mesodermal development, in comparison to control-iPSCs. Additionally, functional and signaling pathway analyses indicate significantly different cell fate determination between PKD-iPSCs and control-iPSCs. Together, the establishment of PKD-specific in vitro models and the illustration of transcriptome features in PKD cells would certainly help us with better understanding of the defects in neural conversion as well as further investigations in the pathogenesis of the PKD disease.

  18. A module of human peripheral blood mononuclear cell transcriptional network containing primitive and differentiation markers is related to specific cardiovascular health variables.

    Science.gov (United States)

    Moldovan, Leni; Anghelina, Mirela; Kantor, Taylor; Jones, Desiree; Ramadan, Enass; Xiang, Yang; Huang, Kun; Kolipaka, Arunark; Malarkey, William; Ghasemzadeh, Nima; Mohler, Peter J; Quyyumi, Arshed; Moldovan, Nicanor I

    2014-01-01

    Peripheral blood mononuclear cells (PBMCs), including rare circulating stem and progenitor cells (CSPCs), have important yet poorly understood roles in the maintenance and repair of blood vessels and perfused organs. Our hypothesis was that the identities and functions of CSPCs in cardiovascular health could be ascertained by analyzing the patterns of their co-expressed markers in unselected PBMC samples. Because gene microarrays had failed to detect many stem cell-associated genes, we performed quantitative real-time PCR to measure the expression of 45 primitive and tissue differentiation markers in PBMCs from healthy and hypertensive human subjects. We compared these expression levels to the subjects' demographic and cardiovascular risk factors, including vascular stiffness. The tested marker genes were expressed in all of samples and organized in hierarchical transcriptional network modules, constructed by a bottom-up approach. An index of gene expression in one of these modules (metagene), defined as the average standardized relative copy numbers of 15 pluripotency and cardiovascular differentiation markers, was negatively correlated (all ptranscriptional network. Furthermore, the coordinated gene expression in these modules can be linked to cardiovascular risk factors and subclinical cardiovascular disease; thus, this measure may be useful for their diagnosis and prognosis.

  19. Transcriptional delay stabilizes bistable gene networks

    Science.gov (United States)

    Gupta, Chinmaya; López, José Manuel; Ott, William; Josić, Krešimir; Bennett, Matthew R.

    2014-01-01

    Transcriptional delay can significantly impact the dynamics of gene networks. Here we examine how such delay affects bistable systems. We investigate several stochastic models of bistable gene networks and find that increasing delay dramatically increases the mean residence times near stable states. To explain this, we introduce a non-Markovian, analytically tractable reduced model. The model shows that stabilization is the consequence of an increased number of failed transitions between stable states. Each of the bistable systems that we simulate behaves in this manner. PMID:23952450

  20. Small-Molecule Inhibition of Rho/MKL/SRF Transcription in Prostate Cancer Cells: Modulation of Cell Cycle, ER Stress, and Metastasis Gene Networks

    Directory of Open Access Journals (Sweden)

    Chris R. Evelyn

    2016-05-01

    Full Text Available Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL and serum response factor (SRF drive metastasis in breast cancer and melanoma. We recently identified a compound, CCG-1423, which blocks Rho/MKL/SRF-mediated transcription and inhibits PC-3 prostate cancer cell invasion. Here, we undertook a genome-wide expression study in PC-3 cells to explore the mechanism and function of this compound. There was significant overlap in the genes modulated by CCG-1423 and Latrunculin B (Lat B, which blocks the Rho/MKL/SRF pathway by preventing actin polymerization. In contrast, the general transcription inhibitor 5,6-dichloro-1-β-d-ribofuranosyl-1H-benzimidazole (DRB showed a markedly different pattern. Effects of CCG-1423 and Lat B on gene expression correlated with literature studies of MKL knock-down. Gene sets involved in DNA synthesis and repair, G1/S transition, and apoptosis were modulated by CCG-1423. It also upregulated genes involved in endoplasmic reticulum stress. Targets of the known Rho target transcription factor family E2F and genes related to melanoma progression and metastasis were strongly suppressed by CCG-1423. These results confirm the ability of our compound to inhibit expression of numerous Rho/MKL-dependent genes and show effects on stress pathways as well. This suggests a novel approach to targeting aggressive cancers and metastasis.

  1. Small-Molecule Inhibition of Rho/MKL/SRF Transcription in Prostate Cancer Cells: Modulation of Cell Cycle, ER Stress, and Metastasis Gene Networks.

    Science.gov (United States)

    Evelyn, Chris R; Lisabeth, Erika M; Wade, Susan M; Haak, Andrew J; Johnson, Craig N; Lawlor, Elizabeth R; Neubig, Richard R

    2016-05-28

    Metastasis is the major cause of cancer deaths and control of gene transcription has emerged as a critical contributing factor. RhoA- and RhoC-induced gene transcription via the actin-regulated transcriptional co-activator megakaryocytic leukemia (MKL) and serum response factor (SRF) drive metastasis in breast cancer and melanoma. We recently identified a compound, CCG-1423, which blocks Rho/MKL/SRF-mediated transcription and inhibits PC-3 prostate cancer cell invasion. Here, we undertook a genome-wide expression study in PC-3 cells to explore the mechanism and function of this compound. There was significant overlap in the genes modulated by CCG-1423 and Latrunculin B (Lat B), which blocks the Rho/MKL/SRF pathway by preventing actin polymerization. In contrast, the general transcription inhibitor 5,6-dichloro-1-β-d-ribofuranosyl-1H-benzimidazole (DRB) showed a markedly different pattern. Effects of CCG-1423 and Lat B on gene expression correlated with literature studies of MKL knock-down. Gene sets involved in DNA synthesis and repair, G1/S transition, and apoptosis were modulated by CCG-1423. It also upregulated genes involved in endoplasmic reticulum stress. Targets of the known Rho target transcription factor family E2F and genes related to melanoma progression and metastasis were strongly suppressed by CCG-1423. These results confirm the ability of our compound to inhibit expression of numerous Rho/MKL-dependent genes and show effects on stress pathways as well. This suggests a novel approach to targeting aggressive cancers and metastasis.

  2. Switching on cilia: transcriptional networks regulating ciliogenesis.

    Science.gov (United States)

    Choksi, Semil P; Lauter, Gilbert; Swoboda, Peter; Roy, Sudipto

    2014-04-01

    Cilia play many essential roles in fluid transport and cellular locomotion, and as sensory hubs for a variety of signal transduction pathways. Despite having a conserved basic morphology, cilia vary extensively in their shapes and sizes, ultrastructural details, numbers per cell, motility patterns and sensory capabilities. Emerging evidence indicates that this diversity, which is intimately linked to the different functions that cilia perform, is in large part programmed at the transcriptional level. Here, we review our understanding of the transcriptional control of ciliary biogenesis, highlighting the activities of FOXJ1 and the RFX family of transcriptional regulators. In addition, we examine how a number of signaling pathways, and lineage and cell fate determinants can induce and modulate ciliogenic programs to bring about the differentiation of distinct cilia types.

  3. Transcriptional networks in response to irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Gidrol, X. [Evry Univ., Lab. of Functional Exploration of Genomes, Service de Genomique Fonctionnelle, CEA, 91 (France)

    2006-07-01

    The main objectives in the laboratory are to characterize human genes of unknown functions which are involved in cell differentiation and in responses to genotoxic compounds, to infer genetic networks of differentiation and response to ionizing radiation. Two topics are specially developed: the first one, cell /siRNA micro-arrays to characterize genes involved in phosphorylation of histone H2AX, the second one genetic networks in differentiation and in response to irradiation. (N.C.)

  4. A systems approach to mapping transcriptional networks controlling surfactant homeostasis

    Directory of Open Access Journals (Sweden)

    Dave Vrushank

    2010-07-01

    Full Text Available Abstract Background Pulmonary surfactant is required for lung function at birth and throughout life. Lung lipid and surfactant homeostasis requires regulation among multi-tiered processes, coordinating the synthesis of surfactant proteins and lipids, their assembly, trafficking, and storage in type II cells of the lung. The mechanisms regulating these interrelated processes are largely unknown. Results We integrated mRNA microarray data with array independent knowledge using Gene Ontology (GO similarity analysis, promoter motif searching, protein interaction and literature mining to elucidate genetic networks regulating lipid related biological processes in lung. A Transcription factor (TF - target gene (TG similarity matrix was generated by integrating data from different analytic methods. A scoring function was built to rank the likely TF-TG pairs. Using this strategy, we identified and verified critical components of a transcriptional network directing lipogenesis, lipid trafficking and surfactant homeostasis in the mouse lung. Conclusions Within the transcriptional network, SREBP, CEBPA, FOXA2, ETSF, GATA6 and IRF1 were identified as regulatory hubs displaying high connectivity. SREBP, FOXA2 and CEBPA together form a common core regulatory module that controls surfactant lipid homeostasis. The core module cooperates with other factors to regulate lipid metabolism and transport, cell growth and development, cell death and cell mediated immune response. Coordinated interactions of the TFs influence surfactant homeostasis and regulate lung function at birth.

  5. A module of human peripheral blood mononuclear cell transcriptional network containing primitive and differentiation markers is related to specific cardiovascular health variables.

    Directory of Open Access Journals (Sweden)

    Leni Moldovan

    Full Text Available Peripheral blood mononuclear cells (PBMCs, including rare circulating stem and progenitor cells (CSPCs, have important yet poorly understood roles in the maintenance and repair of blood vessels and perfused organs. Our hypothesis was that the identities and functions of CSPCs in cardiovascular health could be ascertained by analyzing the patterns of their co-expressed markers in unselected PBMC samples. Because gene microarrays had failed to detect many stem cell-associated genes, we performed quantitative real-time PCR to measure the expression of 45 primitive and tissue differentiation markers in PBMCs from healthy and hypertensive human subjects. We compared these expression levels to the subjects' demographic and cardiovascular risk factors, including vascular stiffness. The tested marker genes were expressed in all of samples and organized in hierarchical transcriptional network modules, constructed by a bottom-up approach. An index of gene expression in one of these modules (metagene, defined as the average standardized relative copy numbers of 15 pluripotency and cardiovascular differentiation markers, was negatively correlated (all p<0.03 with age (R2 = -0.23, vascular stiffness (R2 = -0.24, and central aortic pressure (R2 = -0.19 and positively correlated with body mass index (R2 = 0.72, in women. The co-expression of three neovascular markers was validated at the single-cell level using mRNA in situ hybridization and immunocytochemistry. The overall gene expression in this cardiovascular module was reduced by 72±22% in the patients compared with controls. However, the compactness of both modules was increased in the patients' samples, which was reflected in reduced dispersion of their nodes' degrees of connectivity, suggesting a more primitive character of the patients' CSPCs. In conclusion, our results show that the relationship between CSPCs and vascular function is encoded in modules of the PBMCs transcriptional

  6. Transcriptional networks inferred from molecular signatures of breast cancer.

    Science.gov (United States)

    Tongbai, Ron; Idelman, Gila; Nordgard, Silje H; Cui, Wenwu; Jacobs, Jonathan L; Haggerty, Cynthia M; Chanock, Stephen J; Børresen-Dale, Anne-Lise; Livingston, Gary; Shaunessy, Patrick; Chiang, Chih-Hung; Kristensen, Vessela N; Bilke, Sven; Gardner, Kevin

    2008-02-01

    Global genomic approaches in cancer research have provided new and innovative strategies for the identification of signatures that differentiate various types of human cancers. Computational analysis of the promoter composition of the genes within these signatures may provide a powerful method for deducing the regulatory transcriptional networks that mediate their collective function. In this study we have systematically analyzed the promoter composition of gene classes derived from previously established genetic signatures that recently have been shown to reliably and reproducibly distinguish five molecular subtypes of breast cancer associated with distinct clinical outcomes. Inferences made from the trends of transcription factor binding site enrichment in the promoters of these gene groups led to the identification of regulatory pathways that implicate discrete transcriptional networks associated with specific molecular subtypes of breast cancer. One of these inferred pathways predicted a role for nuclear factor-kappaB in a novel feed-forward, self-amplifying, autoregulatory module regulated by the ERBB family of growth factor receptors. The existence of this pathway was verified in vivo by chromatin immunoprecipitation and shown to be deregulated in breast cancer cells overexpressing ERBB2. This analysis indicates that approaches of this type can provide unique insights into the differential regulatory molecular programs associated with breast cancer and will aid in identifying specific transcriptional networks and pathways as potential targets for tumor subtype-specific therapeutic intervention.

  7. Deconstructing p53 transcriptional networks in tumor suppression.

    Science.gov (United States)

    Bieging, Kathryn T; Attardi, Laura D

    2012-02-01

    p53 is a pivotal tumor suppressor that induces apoptosis, cell-cycle arrest and senescence in response to stress signals. Although p53 transcriptional activation is important for these responses, the mechanisms underlying tumor suppression have been elusive. To date, no single or compound mouse knockout of specific p53 target genes has recapitulated the dramatic tumor predisposition that characterizes p53-null mice. Recently, however, analysis of knock-in mice expressing p53 transactivation domain mutants has revealed a group of primarily novel direct p53 target genes that may mediate tumor suppression in vivo. We present here an overview of well-known p53 target genes and the tumor phenotypes of the cognate knockout mice, and address the recent identification of new p53 transcriptional targets and how they enhance our understanding of p53 transcriptional networks central for tumor suppression.

  8. Id3 Maintains Foxp3 Expression in Regulatory T Cells by Controlling a Transcriptional Network of E47, Spi-B, and SOCS3.

    Science.gov (United States)

    Rauch, Katharina S; Hils, Miriam; Lupar, Ekaterina; Minguet, Susana; Sigvardsson, Mikael; Rottenberg, Martin E; Izcue, Ana; Schachtrup, Christian; Schachtrup, Kristina

    2016-12-13

    The transcription factor Foxp3 dominantly controls regulatory T (Treg) cell function, and only its continuous expression guarantees the maintenance of full Treg cell-suppressive capacity. However, transcriptional regulators maintaining Foxp3 transcription are incompletely described. Here, we report that high E47 transcription factor activity in Treg cells resulted in unstable Foxp3 expression. Under homeostatic conditions, Treg cells expressed high levels of the E47 antagonist Id3, thus restricting E47 activity and maintaining Foxp3 expression. In contrast, stimulation of Id3-deficient or E47-overexpressing Treg cells resulted in the loss of Foxp3 expression in a subset of Treg cells in vivo and in vitro. Mechanistic analysis indicated that E47 activated expression of the transcription factor Spi-B and the suppressor of cytokine signaling 3 (SOCS3), which both downregulated Foxp3 expression. These findings demonstrate that the balance of Id3 and E47 controls the maintenance of Foxp3 expression in Treg cells and, thus, contributes to Treg cell plasticity.

  9. Bone Marrow Adipocytes Facilitate Fatty Acid Oxidation Activating AMPK and a Transcriptional Network Supporting Survival of Acute Monocytic Leukemia Cells.

    Science.gov (United States)

    Tabe, Yoko; Yamamoto, Shinichi; Saitoh, Kaori; Sekihara, Kazumasa; Monma, Norikazu; Ikeo, Kazuho; Mogushi, Kaoru; Shikami, Masato; Ruvolo, Vivian; Ishizawa, Jo; Hail, Numsen; Kazuno, Saiko; Igarashi, Mamoru; Matsushita, Hiromichi; Yamanaka, Yasunari; Arai, Hajime; Nagaoka, Isao; Miida, Takashi; Hayashizaki, Yoshihide; Konopleva, Marina; Andreeff, Michael

    2017-03-15

    Leukemia cells in the bone marrow must meet the biochemical demands of increased cell proliferation and also survive by continually adapting to fluctuations in nutrient and oxygen availability. Thus, targeting metabolic abnormalities in leukemia cells located in the bone marrow is a novel therapeutic approach. In this study, we investigated the metabolic role of bone marrow adipocytes in supporting the growth of leukemic blasts. Prevention of nutrient starvation-induced apoptosis of leukemic cells by bone marrow adipocytes, as well as the metabolic and molecular mechanisms involved in this process, was investigated using various analytic techniques. In acute monocytic leukemia (AMoL) cells, the prevention of spontaneous apoptosis by bone marrow adipocytes was associated with an increase in fatty acid β-oxidation (FAO) along with the upregulation of PPARγ, FABP4, CD36, and BCL2 genes. In AMoL cells, bone marrow adipocyte coculture increased adiponectin receptor gene expression and its downstream target stress response kinase AMPK, p38 MAPK with autophagy activation, and upregulated antiapoptotic chaperone HSPs. Inhibition of FAO disrupted metabolic homeostasis, increased reactive oxygen species production, and induced the integrated stress response mediator ATF4 and apoptosis in AMoL cells cocultured with bone marrow adipocytes. Our results suggest that bone marrow adipocytes support AMoL cell survival by regulating their metabolic energy balance and that the disruption of FAO in bone marrow adipocytes may be an alternative, novel therapeutic strategy for AMoL therapy. Cancer Res; 77(6); 1453-64. ©2017 AACR.

  10. A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation

    OpenAIRE

    Wontakal, Sandeep N.; Guo, Xingyi; Smith, Cameron; MacCarthy, Thomas; Emery H Bresnick; Bergman, Aviv; Snyder, Michael P.; Weissman, Sherman M.; Zheng, Deyou; Skoultchi, Arthur I.

    2012-01-01

    Two mechanisms that play important roles in cell fate decisions are control of a “core transcriptional network” and repression of alternative transcriptional programs by antagonizing transcription factors. Whether these two mechanisms operate together is not known. Here we report that GATA-1, SCL, and Klf1 form an erythroid core transcriptional network by co-occupying >300 genes. Importantly, we find that PU.1, a negative regulator of terminal erythroid differentiation, is a highly integrated...

  11. Systematic genetic analysis of transcription factors to map the fission yeast transcription-regulatory network.

    Science.gov (United States)

    Chua, Gordon

    2013-12-01

    Mapping transcriptional-regulatory networks requires the identification of target genes, binding specificities and signalling pathways of transcription factors. However, the characterization of each transcription factor sufficiently for deciphering such networks remains laborious. The recent availability of overexpression and deletion strains for almost all of the transcription factor genes in the fission yeast Schizosaccharomyces pombe provides a valuable resource to better investigate transcription factors using systematic genetics. In the present paper, I review and discuss the utility of these strain collections combined with transcriptome profiling and genome-wide chromatin immunoprecipitation to identify the target genes of transcription factors.

  12. T cell post-transcriptional miRNA-mRNA interaction networks identify targets associated with susceptibility/resistance to collagen-induced arthritis.

    Directory of Open Access Journals (Sweden)

    Paula B Donate

    Full Text Available BACKGROUND: Due to recent studies indicating that the deregulation of microRNAs (miRNAs in T cells contributes to increased severity of rheumatoid arthritis, we hypothesized that deregulated miRNAs may interact with key mRNA targets controlling the function or differentiation of these cells in this disease. METHODOLOGY/PRINCIPAL FINDINGS: To test our hypothesis, we used microarrays to survey, for the first time, the expression of all known mouse miRNAs in parallel with genome-wide mRNAs in thymocytes and naïve and activated peripheral CD3(+ T cells from two mouse strains the DBA-1/J strain (MHC-H2q, which is susceptible to collagen induced arthritis (CIA, and the DBA-2/J strain (MHC-H2d, which is resistant. Hierarchical clustering of data showed the several T cell miRNAs and mRNAs differentially expressed between the mouse strains in different stages of immunization with collagen. Bayesian statistics using the GenMir(++ algorithm allowed reconstruction of post-transcriptional miRNA-mRNA interaction networks for target prediction. We revealed the participation of miR-500, miR-202-3p and miR-30b*, which established interactions with at least one of the following mRNAs: Rorc, Fas, Fasl, Il-10 and Foxo3. Among the interactions that were validated by calculating the minimal free-energy of base pairing between the miRNA and the 3'UTR of the mRNA target and luciferase assay, we highlight the interaction of miR-30b*-Rorc mRNA because the mRNA encodes a protein implicated in pro-inflammatory Th17 cell differentiation (Rorγt. FACS analysis revealed that Rorγt protein levels and Th17 cell counts were comparatively reduced in the DBA-2/J strain. CONCLUSIONS/SIGNIFICANCE: This result showed that the miRNAs and mRNAs identified in this study represent new candidates regulating T cell function and controlling susceptibility and resistance to CIA.

  13. Transcriptional network control of normal and leukaemic haematopoiesis.

    Science.gov (United States)

    Sive, Jonathan I; Göttgens, Berthold

    2014-12-10

    Transcription factors (TFs) play a key role in determining the gene expression profiles of stem/progenitor cells, and defining their potential to differentiate into mature cell lineages. TF interactions within gene-regulatory networks are vital to these processes, and dysregulation of these networks by TF overexpression, deletion or abnormal gene fusions have been shown to cause malignancy. While investigation of these processes remains a challenge, advances in genome-wide technologies and growing interactions between laboratory and computational science are starting to produce increasingly accurate network models. The haematopoietic system provides an attractive experimental system to elucidate gene regulatory mechanisms, and allows experimental investigation of both normal and dysregulated networks. In this review we examine the principles of TF-controlled gene regulatory networks and the key experimental techniques used to investigate them. We look in detail at examples of how these approaches can be used to dissect out the regulatory mechanisms controlling normal haematopoiesis, as well as the dysregulated networks associated with haematological malignancies.

  14. Modular composition of gene transcription networks.

    Directory of Open Access Journals (Sweden)

    Andras Gyorgy

    2014-03-01

    Full Text Available Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.

  15. Modular composition of gene transcription networks.

    Science.gov (United States)

    Gyorgy, Andras; Del Vecchio, Domitilla

    2014-03-01

    Predicting the dynamic behavior of a large network from that of the composing modules is a central problem in systems and synthetic biology. Yet, this predictive ability is still largely missing because modules display context-dependent behavior. One cause of context-dependence is retroactivity, a phenomenon similar to loading that influences in non-trivial ways the dynamic performance of a module upon connection to other modules. Here, we establish an analysis framework for gene transcription networks that explicitly accounts for retroactivity. Specifically, a module's key properties are encoded by three retroactivity matrices: internal, scaling, and mixing retroactivity. All of them have a physical interpretation and can be computed from macroscopic parameters (dissociation constants and promoter concentrations) and from the modules' topology. The internal retroactivity quantifies the effect of intramodular connections on an isolated module's dynamics. The scaling and mixing retroactivity establish how intermodular connections change the dynamics of connected modules. Based on these matrices and on the dynamics of modules in isolation, we can accurately predict how loading will affect the behavior of an arbitrary interconnection of modules. We illustrate implications of internal, scaling, and mixing retroactivity on the performance of recurrent network motifs, including negative autoregulation, combinatorial regulation, two-gene clocks, the toggle switch, and the single-input motif. We further provide a quantitative metric that determines how robust the dynamic behavior of a module is to interconnection with other modules. This metric can be employed both to evaluate the extent of modularity of natural networks and to establish concrete design guidelines to minimize retroactivity between modules in synthetic systems.

  16. Transcriptional network of androgen receptor in prostate cancer progression.

    Science.gov (United States)

    Takayama, Ken-ichi; Inoue, Satoshi

    2013-08-01

    The androgen receptor belongs to the nuclear receptor superfamily and functions as a ligand-dependent transcription factor. It binds to the androgen responsive element and recruits coregulatory factors to modulate gene transcription. In addition, the androgen receptor interacts with other transcription factors, such as forkhead box A1, and other oncogenic signaling pathway molecules that bind deoxyribonucleic acid and regulate transcription. Androgen receptor signaling plays an important role in the development of prostate cancer. Prostate cancer cells proliferate in an androgen-dependent manner, and androgen receptor blockade is effective in prostate cancer therapy. However, patients often progress to castration-resistant prostate cancer with elevated androgen receptor expression and hypersensitivity to androgen. Recently, comprehensive analysis tools, such as complementary DNA microarray, chromatin immunoprecipitation-on-chip and chromatin immunoprecipitation-sequence, have described the androgen-mediated diverse transcriptional program and gene networks in prostate cancer. Furthermore, functional and clinical studies have shown that some of the androgen receptor-regulated genes could be prognostic markers and potential therapeutic targets for the treatment of prostate cancer, particularly castration-resistant prostate cancer. Thus, identifying androgen receptor downstream signaling events and investigating the regulation of androgen receptor activity is critical for understanding the mechanism of carcinogenesis and progression to castration-resistant prostate cancer.

  17. Power graph compression reveals dominant relationships in genetic transcription networks.

    Science.gov (United States)

    Ahnert, Sebastian E

    2013-11-01

    We introduce a framework for the discovery of dominant relationship patterns in transcription networks, by compressing the network into a power graph with overlapping power nodes. Our application of this approach to the transcription networks of S. cerevisiae and E. coli, paired with GO term enrichment analysis, provides a highly informative overview of the most prominent relationships in the gene regulatory networks of these two organisms.

  18. ZNF804A Transcriptional Networks in Differentiating Neurons Derived from Induced Pluripotent Stem Cells of Human Origin.

    Directory of Open Access Journals (Sweden)

    Jian Chen

    Full Text Available ZNF804A (Zinc Finger Protein 804A has been identified as a candidate gene for schizophrenia (SZ, autism spectrum disorders (ASD, and bipolar disorder (BD in replicated genome wide association studies (GWAS and by copy number variation (CNV analysis. Although its function has not been well-characterized, ZNF804A contains a C2H2-type zinc-finger domain, suggesting that it has DNA binding properties, and consequently, a role in regulating gene expression. To further explore the role of ZNF804A on gene expression and its downstream targets, we used a gene knockdown (KD approach to reduce its expression in neural progenitor cells (NPCs derived from induced pluripotent stem cells (iPSCs. KD was accomplished by RNA interference (RNAi using lentiviral particles containing shRNAs that target ZNF804A mRNA. Stable transduced NPC lines were generated after puromycin selection. A control cell line expressing a random (scrambled shRNA was also generated. Neuronal differentiation was induced, RNA was harvested after 14 days and transcriptome analysis was carried out using RNA-seq. 1815 genes were found to be differentially expressed at a nominally significant level (p<0.05; 809 decreased in expression in the KD samples, while 1106 increased. Of these, 370 achieved genome wide significance (FDR<0.05; 125 were lower in the KD samples, 245 were higher. Pathway analysis showed that genes involved in interferon-signaling were enriched among those that were down-regulated in the KD samples. Correspondingly, ZNF804A KD was found to affect interferon-alpha 2 (IFNA2-mediated gene expression. The findings suggest that ZNF804A may affect a differentiating neuron's response to inflammatory cytokines, which is consistent with models of SZ and ASD that support a role for infectious disease, and/or autoimmunity in a subgroup of patients.

  19. ZNF804A Transcriptional Networks in Differentiating Neurons Derived from Induced Pluripotent Stem Cells of Human Origin.

    Science.gov (United States)

    Chen, Jian; Lin, Mingyan; Hrabovsky, Anastasia; Pedrosa, Erika; Dean, Jason; Jain, Swati; Zheng, Deyou; Lachman, Herbert M

    2015-01-01

    ZNF804A (Zinc Finger Protein 804A) has been identified as a candidate gene for schizophrenia (SZ), autism spectrum disorders (ASD), and bipolar disorder (BD) in replicated genome wide association studies (GWAS) and by copy number variation (CNV) analysis. Although its function has not been well-characterized, ZNF804A contains a C2H2-type zinc-finger domain, suggesting that it has DNA binding properties, and consequently, a role in regulating gene expression. To further explore the role of ZNF804A on gene expression and its downstream targets, we used a gene knockdown (KD) approach to reduce its expression in neural progenitor cells (NPCs) derived from induced pluripotent stem cells (iPSCs). KD was accomplished by RNA interference (RNAi) using lentiviral particles containing shRNAs that target ZNF804A mRNA. Stable transduced NPC lines were generated after puromycin selection. A control cell line expressing a random (scrambled) shRNA was also generated. Neuronal differentiation was induced, RNA was harvested after 14 days and transcriptome analysis was carried out using RNA-seq. 1815 genes were found to be differentially expressed at a nominally significant level (p<0.05); 809 decreased in expression in the KD samples, while 1106 increased. Of these, 370 achieved genome wide significance (FDR<0.05); 125 were lower in the KD samples, 245 were higher. Pathway analysis showed that genes involved in interferon-signaling were enriched among those that were down-regulated in the KD samples. Correspondingly, ZNF804A KD was found to affect interferon-alpha 2 (IFNA2)-mediated gene expression. The findings suggest that ZNF804A may affect a differentiating neuron's response to inflammatory cytokines, which is consistent with models of SZ and ASD that support a role for infectious disease, and/or autoimmunity in a subgroup of patients.

  20. Inference of self-regulated transcriptional networks by comparative genomics.

    Science.gov (United States)

    Cornish, Joseph P; Matthews, Fialelei; Thomas, Julien R; Erill, Ivan

    2012-01-01

    The assumption of basic properties, like self-regulation, in simple transcriptional regulatory networks can be exploited to infer regulatory motifs from the growing amounts of genomic and meta-genomic data. These motifs can in principle be used to elucidate the nature and scope of transcriptional networks through comparative genomics. Here we assess the feasibility of this approach using the SOS regulatory network of Gram-positive bacteria as a test case. Using experimentally validated data, we show that the known regulatory motif can be inferred through the assumption of self-regulation. Furthermore, the inferred motif provides a more robust search pattern for comparative genomics than the experimental motifs defined in reference organisms. We take advantage of this robustness to generate a functional map of the SOS response in Gram-positive bacteria. Our results reveal definite differences in the composition of the LexA regulon between Firmicutes and Actinobacteria, and confirm that regulation of cell-division inhibition is a widespread characteristic of this network among Gram-positive bacteria.

  1. Navigating the transcriptional roadmap regulating plant secondary cell wall deposition

    Directory of Open Access Journals (Sweden)

    Steven Grant Hussey

    2013-08-01

    Full Text Available The current status of lignocellulosic biomass as an invaluable resource in industry, agriculture and health has spurred increased interest in understanding the transcriptional regulation of secondary cell wall (SCW biosynthesis. The last decade of research has revealed an extensive network of NAC, MYB and other families of transcription factors regulating Arabidopsis SCW biosynthesis, and numerous studies have explored SCW-related transcription factors in other dicots and monocots. Whilst the general structure of the Arabidopsis network has been a topic of several reviews, they have not comprehensively represented the detailed protein-DNA and protein-protein interactions described in the literature, and an understanding of network dynamics and functionality has not yet been achieved for SCW formation. Furthermore the methodologies employed in studies of SCW transcriptional regulation have not received much attention, especially in the case of non-model organisms. In this review, we have reconstructed the most exhaustive literature-based network representations to date of SCW transcriptional regulation in Arabidopsis. We include a manipulable Cytoscape representation of the Arabidopsis SCW transcriptional network to aid in future studies, along with a list of supporting literature for each documented interaction. Amongst other topics, we discuss the various components of the network, its evolutionary conservation in plants, putative modules and dynamic mechanisms that may influence network function, and the approaches that have been employed in network inference. Future research should aim to better understand network function and its response to dynamic perturbations, whilst the development and application of genome-wide approaches such as ChIP-seq and systems genetics are in progress for the study of SCW transcriptional regulation in non-model organisms.

  2. Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks.

    Directory of Open Access Journals (Sweden)

    Karl Fogelmark

    Full Text Available Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated.To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved networks, and predictions are validated against the transcriptional network of E. coli.We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks.

  3. Transcriptional regulation of dendritic cell diversity.

    Science.gov (United States)

    Chopin, Michaël; Allan, Rhys S; Belz, Gabrielle T

    2012-01-01

    Dendritic cells (DCs) are specialized antigen presenting cells that are exquisitely adapted to sense pathogens and induce the development of adaptive immune responses. They form a complex network of phenotypically and functionally distinct subsets. Within this network, individual DC subsets display highly specific roles in local immunosurveillance, migration, and antigen presentation. This division of labor amongst DCs offers great potential to tune the immune response by harnessing subset-specific attributes of DCs in the clinical setting. Until recently, our understanding of DC subsets has been limited and paralleled by poor clinical translation and efficacy. We have now begun to unravel how different DC subsets develop within a complex multilayered system. These findings open up exciting possibilities for targeted manipulation of DC subsets. Furthermore, ground-breaking developments overcoming a major translational obstacle - identification of similar DC populations in mouse and man - now sets the stage for significant advances in the field. Here we explore the determinants that underpin cellular and transcriptional heterogeneity within the DC network, how these influence DC distribution and localization at steady-state, and the capacity of DCs to present antigens via direct or cross-presentation during pathogen infection.

  4. Versatile RNA-sensing transcriptional regulators for engineering genetic networks.

    Science.gov (United States)

    Lucks, Julius B; Qi, Lei; Mutalik, Vivek K; Wang, Denise; Arkin, Adam P

    2011-05-24

    The widespread natural ability of RNA to sense small molecules and regulate genes has become an important tool for synthetic biology in applications as diverse as environmental sensing and metabolic engineering. Previous work in RNA synthetic biology has engineered RNA mechanisms that independently regulate multiple targets and integrate regulatory signals. However, intracellular regulatory networks built with these systems have required proteins to propagate regulatory signals. In this work, we remove this requirement and expand the RNA synthetic biology toolkit by engineering three unique features of the plasmid pT181 antisense-RNA-mediated transcription attenuation mechanism. First, because the antisense RNA mechanism relies on RNA-RNA interactions, we show how the specificity of the natural system can be engineered to create variants that independently regulate multiple targets in the same cell. Second, because the pT181 mechanism controls transcription, we show how independently acting variants can be configured in tandem to integrate regulatory signals and perform genetic logic. Finally, because both the input and output of the attenuator is RNA, we show how these variants can be configured to directly propagate RNA regulatory signals by constructing an RNA-meditated transcriptional cascade. The combination of these three features within a single RNA-based regulatory mechanism has the potential to simplify the design and construction of genetic networks by directly propagating signals as RNA molecules.

  5. Current and emerging approaches to define intestinal epithelium-specific transcriptional networks

    DEFF Research Database (Denmark)

    Olsen, Anders Krûger; Boyd, Mette; Danielsen, Erik Thomas

    2012-01-01

    Upon developmental or environmental cues, the composition of transcription factors in a transcriptional regulatory network is deeply implicated in controlling the signature of the gene expression and thereby specifies the cell- or tissue-type. Novel methods including ChIP-chip and ChIP-Seq have b...

  6. Current and emerging approaches to define intestinal epithelium-specific transcriptional networks

    DEFF Research Database (Denmark)

    Olsen, Anders Krüger; Boyd, Mette; Danielsen, Erik Thomas

    2012-01-01

    Upon developmental or environmental cues, the composition of transcription factors in a transcriptional regulatory network is deeply implicated in controlling the signature of the gene expression and thereby specifies the cell or tissue type. Novel methods including ChIP-chip and ChIP-Seq have be...

  7. Trimming of mammalian transcriptional networks using network component analysis

    Directory of Open Access Journals (Sweden)

    Liao James C

    2010-10-01

    Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm

  8. Uncovering transcriptional regulation of metabolism by using metabolic network topology

    DEFF Research Database (Denmark)

    Patil, Kiran Raosaheb; Nielsen, Jens

    2005-01-01

    therefore developed an algorithm that is based on hypothesis-driven data analysis to uncover the transcriptional regulatory architecture of metabolic networks. By using information on the metabolic network topology from genome-scale metabolic reconstruction, we show that it is possible to reveal patterns...... in the metabolic network that follow a common transcriptional response. Thus, the algorithm enables identification of so-called reporter metabolites (metabolites around which the most significant transcriptional changes occur) and a set of connected genes with significant and coordinated response to genetic...... changes induced by complex regulatory mechanisms coordinating the activity of different metabolic pathways. It is difficult to map such global transcriptional responses by using traditional methods, because many genes in the metabolic network have relatively small changes at their transcription level. We...

  9. Modeling microRNA-transcription factor networks in cancer.

    Science.gov (United States)

    Aguda, Baltazar D

    2013-01-01

    An increasing number of transcription factors (TFs) and microRNAs (miRNAs) is known to form feedback loops (FBLs) of interactions where a TF positively or negatively regulates the expression of a miRNA, and the miRNA suppresses the translation of the TF messenger RNA. FBLs are potential sources of instability in a gene regulatory network. Positive FBLs can give rise to switching behaviors while negative FBLs can generate periodic oscillations. This chapter presents documented examples of FBLs and their relevance to stem cell renewal and differentiation in gliomas. Feed-forward loops (FFLs) are only discussed briefly because they do not affect network stability unless they are members of cycles. A primer on qualitative network stability analysis is given and then used to demonstrate the network destabilizing role of FBLs. Steps in model formulation and computer simulations are illustrated using the miR-17-92/Myc/E2F network as an example. This example possesses both negative and positive FBLs.

  10. Topology of transcriptional regulatory networks: testing and improving.

    Directory of Open Access Journals (Sweden)

    Dicle Hasdemir

    Full Text Available With the increasing amount and complexity of data generated in biological experiments it is becoming necessary to enhance the performance and applicability of existing statistical data analysis methods. This enhancement is needed for the hidden biological information to be better resolved and better interpreted. Towards that aim, systematic incorporation of prior information in biological data analysis has been a challenging problem for systems biology. Several methods have been proposed to integrate data from different levels of information most notably from metabolomics, transcriptomics and proteomics and thus enhance biological interpretation. However, in order not to be misled by the dominance of incorrect prior information in the analysis, being able to discriminate between competing prior information is required. In this study, we show that discrimination between topological information in competing transcriptional regulatory network models is possible solely based on experimental data. We use network topology dependent decomposition of synthetic gene expression data to introduce both local and global discriminating measures. The measures indicate how well the gene expression data can be explained under the constraints of the model network topology and how much each regulatory connection in the model refuses to be constrained. Application of the method to the cell cycle regulatory network of Saccharomyces cerevisiae leads to the prediction of novel regulatory interactions, improving the information content of the hypothesized network model.

  11. Cytokines interleukin-1beta and tumor necrosis factor-alpha regulate different transcriptional and alternative splicing networks in primary beta-cells

    DEFF Research Database (Denmark)

    Ortis, Fernanda; Naamane, Najib; Flamez, Daisy

    2010-01-01

    , and global gene expression was analyzed by microarray. Key results were confirmed by RT-PCR, and small-interfering RNAs were used to investigate the mechanistic role of novel and relevant transcription factors identified by pathway analysis. RESULTS Nearly 16,000 transcripts were detected as present in beta...... of genes involved in the maintenance of beta-cell phenotype and growth/regeneration. Cytokines induced hypoxia-inducible factor-alpha, which in this context has a proapoptotic role. Cytokines also modified the expression of >20 genes involved in RNA splicing, and exon array analysis showed cytokine......-induced changes in alternative splicing of >50% of the cytokine-modified genes. CONCLUSIONS: The present study doubles the number of known genes expressed in primary beta-cells, modified or not by cytokines, and indicates the biological role for several novel cytokine-modified pathways in beta-cells. It also...

  12. Developmental transcriptional networks are required to maintain neuronal subtype identity in the mature nervous system.

    Directory of Open Access Journals (Sweden)

    Kevin T Eade

    Full Text Available During neurogenesis, transcription factors combinatorially specify neuronal fates and then differentiate subtype identities by inducing subtype-specific gene expression profiles. But how is neuronal subtype identity maintained in mature neurons? Modeling this question in two Drosophila neuronal subtypes (Tv1 and Tv4, we test whether the subtype transcription factor networks that direct differentiation during development are required persistently for long-term maintenance of subtype identity. By conditional transcription factor knockdown in adult Tv neurons after normal development, we find that most transcription factors within the Tv1/Tv4 subtype transcription networks are indeed required to maintain Tv1/Tv4 subtype-specific gene expression in adults. Thus, gene expression profiles are not simply "locked-in," but must be actively maintained by persistent developmental transcription factor networks. We also examined the cross-regulatory relationships between all transcription factors that persisted in adult Tv1/Tv4 neurons. We show that certain critical cross-regulatory relationships that had existed between these transcription factors during development were no longer present in the mature adult neuron. This points to key differences between developmental and maintenance transcriptional regulatory networks in individual neurons. Together, our results provide novel insight showing that the maintenance of subtype identity is an active process underpinned by persistently active, combinatorially-acting, developmental transcription factors. These findings have implications for understanding the maintenance of all long-lived cell types and the functional degeneration of neurons in the aging brain.

  13. Evidence for a common evolutionary rate in metazoan transcriptional networks.

    Science.gov (United States)

    Carvunis, Anne-Ruxandra; Wang, Tina; Skola, Dylan; Yu, Alice; Chen, Jonathan; Kreisberg, Jason F; Ideker, Trey

    2015-12-18

    Genome sequences diverge more rapidly in mammals than in other animal lineages, such as birds or insects. However, the effect of this rapid divergence on transcriptional evolution remains unclear. Recent reports have indicated a faster divergence of transcription factor binding in mammals than in insects, but others found the reverse for mRNA expression. Here, we show that these conflicting interpretations resulted from differing methodologies. We performed an integrated analysis of transcriptional network evolution by examining mRNA expression, transcription factor binding and cis-regulatory motifs across >25 animal species, including mammals, birds and insects. Strikingly, we found that transcriptional networks evolve at a common rate across the three animal lineages. Furthermore, differences in rates of genome divergence were greatly reduced when restricting comparisons to chromatin-accessible sequences. The evolution of transcription is thus decoupled from the global rate of genome sequence evolution, suggesting that a small fraction of the genome regulates transcription.

  14. Identification of transcriptional regulatory networks specific to pilocytic astrocytoma

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    Gutmann David H

    2011-07-01

    Full Text Available Abstract Background Pilocytic Astrocytomas (PAs are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours. Methods RNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization. Results In this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions. Conclusions These results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic

  15. AURA 2: Empowering discovery of post-transcriptional networks.

    Science.gov (United States)

    Dassi, Erik; Re, Angela; Leo, Sara; Tebaldi, Toma; Pasini, Luigi; Peroni, Daniele; Quattrone, Alessandro

    2014-01-01

    Post-transcriptional regulation (PTR) of gene expression is now recognized as a major determinant of cell phenotypes. The recent availability of methods to map protein-RNA interactions in entire transcriptomes such as RIP, CLIP and their variants, together with global polysomal and ribosome profiling techniques, are driving the exponential accumulation of vast amounts of data on mRNA contacts in cells, and of corresponding predictions of PTR events. However, this exceptional quantity of information cannot be exploited at its best to reconstruct potential PTR networks, as it still lies scattered throughout several databases and in isolated reports of single interactions. To address this issue, we developed the second and vastly enhanced version of the Atlas of UTR Regulatory Activity (AURA 2), a meta-database centered on mapping interaction of trans-factors with human and mouse UTRs. AURA 2 includes experimentally demonstrated binding sites for RBPs, ncRNAs, thousands of cis-elements, variations, RNA epigenetics data and more. Its user-friendly interface offers various data-mining features including co-regulation search, network generation and regulatory enrichment testing. Gene expression profiles for many tissues and cell lines can be also combined with these analyses to display only the interactions possible in the system under study. AURA 2 aims at becoming a valuable toolbox for PTR studies and at tracing the road for how PTR network-building tools should be designed. AURA 2 is available at http://aura.science.unitn.it.

  16. General trends in the evolution of prokaryotic transcriptional regulatory networks.

    Science.gov (United States)

    Madan Babu, M; Balaji, S; Aravind, L

    2007-01-01

    Gene expression in organisms is controlled by regulatory proteins termed transcription factors, which recognize and bind to specific nucleotide sequences. Over the years, considerable information has accumulated on the regulatory interactions between transcription factors and their target genes in various model prokaryotes, such as Escherichia coli and Bacillus subtilis. This has allowed the representation of this information in the form of a directed graph, which is commonly referred to as the transcriptional regulatory network. The network representation provides us with an excellent conceptual framework to understand the structure of the transcriptional regulation, both at local and global levels of organization. Several studies suggest that the transcriptional network inferred from model organisms may be approximated by a scale-free topology, which in turn implies the presence of a relatively small group of highly connected regulators (hubs or global regulators). While the graph theoretical principles have been applied to infer various properties of such networks, there have been few studies that have actually investigated the evolution of the transcriptional regulatory networks across diverse organisms. Using recently developed computational methods that exploit various evolutionary principles, we have attempted to reconstruct and compare these networks across a wide-range of prokaryotes. This has provided several insights on the modification and diversification of network structures of various organisms in course of evolution. Firstly, we observed that target genes show a much higher level of conservation than their transcriptional regulators. This in turn suggested that the same set of functions could be differently controlled across diverse organisms, contributing significantly to their adaptive radiations. In particular, at the local level of network structure, organism-specific optimization of the transcription network has evolved primarily via tinkering

  17. The effect of negative feedback on noise propagation in transcriptional gene networks

    Science.gov (United States)

    Hooshangi, Sara; Weiss, Ron

    2006-06-01

    This paper analyzes how the delay and repression strength of negative feedback in single-gene and multigene transcriptional networks influences intrinsic noise propagation and oscillatory behavior. We simulate a variety of transcriptional networks using a stochastic model and report two main findings. First, intrinsic noise is not attenuated by the addition of negative or positive feedback to transcriptional cascades. Second, for multigene negative feedback networks, synchrony in oscillations among a cell population can be improved by increasing network depth and tightening the regulation at one of the repression stages. Our long term goal is to understand how the noise characteristics of complex networks can be derived from the properties of modules that are used to compose these networks.

  18. Transcriptional Network Architecture of Breast Cancer Molecular Subtypes

    Directory of Open Access Journals (Sweden)

    Guillermo de Anda-Jáuregui

    2016-11-01

    Full Text Available Breast cancer heterogeneity is evident at the clinical, histological and molecular level. High throughput technologies allowed the identification of intrinsic subtypes that capture transcriptional differences among tumors. A remaining question is whether said differences are associated to a particular transcriptional program which involves different connections between the same molecules. In other words, whether particular transcriptional network architectures can be linked to specific phenotypes.In this work we infer, construct and analyze transcriptional networks from whole-genome gene expression microarrays, by using an information theory approach. We use 493 samples of primary breast cancer tissue classified in four molecular subtypes: Luminal A, Luminal B, Basal and HER2-enriched. For comparison, a network for non-tumoral mammary tissue (61 samples is also inferred and analyzed.Transcriptional networks present particular architectures in each breast cancer subtype as well as in the non-tumor breast tissue. We find substantial differences between the non-tumor network and those networks inferred from cancer samples, in both structure and gene composition. More importantly, we find specific network architectural features associated to each breast cancer subtype. Based on breast cancer networks' centrality, we identify genes previously associated to the disease, either, generally (i.e. CNR2 or to a particular subtype (such as LCK. Similarly, we identify LUZP4, a gene barely explored in breast cancer, playing a role in transcriptional networks with subtype-specific relevance.With this approach we observe architectural differences between cancer and non-cancer at network level, as well as differences between cancer subtype networks which might be associated with breast cancer heterogeneity. The centrality measures of these networks allow us to identify genes with potential biomedical implications to breast cancer.

  19. Transcriptional Network Architecture of Breast Cancer Molecular Subtypes.

    Science.gov (United States)

    de Anda-Jáuregui, Guillermo; Velázquez-Caldelas, Tadeo E; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2016-01-01

    Breast cancer heterogeneity is evident at the clinical, histological and molecular level. High throughput technologies allowed the identification of intrinsic subtypes that capture transcriptional differences among tumors. A remaining question is whether said differences are associated to a particular transcriptional program which involves different connections between the same molecules. In other words, whether particular transcriptional network architectures can be linked to specific phenotypes. In this work we infer, construct and analyze transcriptional networks from whole-genome gene expression microarrays, by using an information theory approach. We use 493 samples of primary breast cancer tissue classified in four molecular subtypes: Luminal A, Luminal B, Basal and HER2-enriched. For comparison, a network for non-tumoral mammary tissue (61 samples) is also inferred and analyzed. Transcriptional networks present particular architectures in each breast cancer subtype as well as in the non-tumor breast tissue. We find substantial differences between the non-tumor network and those networks inferred from cancer samples, in both structure and gene composition. More importantly, we find specific network architectural features associated to each breast cancer subtype. Based on breast cancer networks' centrality, we identify genes previously associated to the disease, either, generally (i.e., CNR2) or to a particular subtype (such as LCK). Similarly, we identify LUZP4, a gene barely explored in breast cancer, playing a role in transcriptional networks with subtype-specific relevance. With this approach we observe architectural differences between cancer and non-cancer at network level, as well as differences between cancer subtype networks which might be associated with breast cancer heterogeneity. The centrality measures of these networks allow us to identify genes with potential biomedical implications to breast cancer.

  20. Transcriptional Network Architecture of Breast Cancer Molecular Subtypes

    Science.gov (United States)

    de Anda-Jáuregui, Guillermo; Velázquez-Caldelas, Tadeo E.; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2016-01-01

    Breast cancer heterogeneity is evident at the clinical, histological and molecular level. High throughput technologies allowed the identification of intrinsic subtypes that capture transcriptional differences among tumors. A remaining question is whether said differences are associated to a particular transcriptional program which involves different connections between the same molecules. In other words, whether particular transcriptional network architectures can be linked to specific phenotypes. In this work we infer, construct and analyze transcriptional networks from whole-genome gene expression microarrays, by using an information theory approach. We use 493 samples of primary breast cancer tissue classified in four molecular subtypes: Luminal A, Luminal B, Basal and HER2-enriched. For comparison, a network for non-tumoral mammary tissue (61 samples) is also inferred and analyzed. Transcriptional networks present particular architectures in each breast cancer subtype as well as in the non-tumor breast tissue. We find substantial differences between the non-tumor network and those networks inferred from cancer samples, in both structure and gene composition. More importantly, we find specific network architectural features associated to each breast cancer subtype. Based on breast cancer networks' centrality, we identify genes previously associated to the disease, either, generally (i.e., CNR2) or to a particular subtype (such as LCK). Similarly, we identify LUZP4, a gene barely explored in breast cancer, playing a role in transcriptional networks with subtype-specific relevance. With this approach we observe architectural differences between cancer and non-cancer at network level, as well as differences between cancer subtype networks which might be associated with breast cancer heterogeneity. The centrality measures of these networks allow us to identify genes with potential biomedical implications to breast cancer. PMID:27920729

  1. Control of transcription by cell size.

    Directory of Open Access Journals (Sweden)

    Chia-Yung Wu

    Full Text Available Cell size increases significantly with increasing ploidy. Differences in cell size and ploidy are associated with alterations in gene expression, although no direct connection has been made between cell size and transcription. Here we show that ploidy-associated changes in gene expression reflect transcriptional adjustment to a larger cell size, implicating cellular geometry as a key parameter in gene regulation. Using RNA-seq, we identified genes whose expression was altered in a tetraploid as compared with the isogenic haploid. A significant fraction of these genes encode cell surface proteins, suggesting an effect of the enlarged cell size on the differential regulation of these genes. To test this hypothesis, we examined expression of these genes in haploid mutants that also produce enlarged size. Surprisingly, many genes differentially regulated in the tetraploid are identically regulated in the enlarged haploids, and the magnitude of change in gene expression correlates with the degree of size enlargement. These results indicate a causal relationship between cell size and transcription, with a size-sensing mechanism that alters transcription in response to size. The genes responding to cell size are enriched for those regulated by two mitogen-activated protein kinase pathways, and components in those pathways were found to mediate size-dependent gene regulation. Transcriptional adjustment to enlarged cell size could underlie other cellular changes associated with polyploidy. The causal relationship between cell size and transcription suggests that cell size homeostasis serves a regulatory role in transcriptome maintenance.

  2. Modeling transcriptional networks in Drosophila development at multiple scales.

    Science.gov (United States)

    Wunderlich, Zeba; DePace, Angela H

    2011-12-01

    Quantitative models of developmental processes can provide insights at multiple scales. Ultimately, models may be particularly informative for key questions about network level behavior during development such as how does the system respond to environmental perturbation, or operate reliably in different genetic backgrounds? The transcriptional networks that pattern the Drosophila embryo have been the subject of numerous quantitative experimental studies coupled to modeling frameworks in recent years. In this review, we describe three studies that consider these networks at different levels of molecular detail and therefore result in different types of insights. We also discuss other developmental transcriptional networks operating in Drosophila, with the goal of highlighting what additional insights they may provide.

  3. The p53 Transcriptional Network Influences Microglia Behavior and Neuroinflammation.

    Science.gov (United States)

    Aloi, Macarena S; Su, Wei; Garden, Gwenn A

    2015-01-01

    The tumor-suppressor protein p53 belongs to a family of proteins that play pivotal roles in multiple cellular functions including cell proliferation, cell death, genome stability, and regulation of inflammation. Neuroinflammation is a common feature of central nervous system (CNS) pathology, and microglia are the specialized resident population of CNS myeloid cells that initiate innate immune responses. Microglia maintain CNS homeostasis through pathogen containment, phagocytosis of debris, and initiation of tissue-repair cascades. However, an unregulated pro-inflammatory response can lead to tissue injury and dysfunction in both acute and chronic inflammatory states. Therefore, regulation of the molecular signals that control the induction, magnitude, and resolution of inflammation are necessary for optimal CNS health. We and others have described a novel mechanism by which p53 transcriptional activity modulates microglia behaviors in vitro and in vivo. Activation of p53 induces expression of microRNAs (miRNAs) that support microglia pro-inflammatory functions and suppress anti-inflammatory and tissue repair behaviors. In this review, we introduce the previously described roles of the p53 signaling network and discuss novel functions of p53 in the microglia-mediated inflammatory response in CNS health and disease. Ultimately, improved understanding of the molecular regulators modulated by p53 transcriptional activity in microglia will enhance the development of rational therapeutic strategies to harness the homeostatic and tissue repair functions of microglia.

  4. Cytokines interleukin-1beta and tumor necrosis factor-alpha regulate different transcriptional and alternative splicing networks in primary beta-cells

    DEFF Research Database (Denmark)

    Ortis, Fernanda; Naamane, Najib; Flamez, Daisy

    2010-01-01

    OBJECTIVE: Cytokines contribute to pancreatic beta-cell death in type 1 diabetes. This effect is mediated by complex gene networks that remain to be characterized. We presently utilized array analysis to define the global expression pattern of genes, including spliced variants, modified by the cy...

  5. DMPD: The interferon signaling network and transcription factor C/EBP-beta. [Dynamic Macrophage Pathway CSML Database

    Lifescience Database Archive (English)

    Full Text Available 18163952 The interferon signaling network and transcription factor C/EBP-beta. Li H..., Gade P, Xiao W, Kalvakolanu DV. Cell Mol Immunol. 2007 Dec;4(6):407-18. (.png) (.svg) (.html) (.csml) Show The... interferon signaling network and transcription factor C/EBP-beta. PubmedID 18163952 Title The interfero

  6. Transcriptional networks and chromatin remodeling controlling adipogenesis

    DEFF Research Database (Denmark)

    Siersbæk, Rasmus; Nielsen, Ronni; Mandrup, Susanne

    2012-01-01

    remodeling have revealed 'snapshots' of this cascade and the chromatin landscape at specific time-points of differentiation. These studies demonstrate that multiple adipogenic transcription factors co-occupy hotspots characterized by an open chromatin structure and specific epigenetic modifications...

  7. Transcription factors regulating B cell fate in the germinal centre.

    Science.gov (United States)

    Recaldin, T; Fear, D J

    2016-01-01

    Diversification of the antibody repertoire is essential for the normal operation of the vertebrate adaptive immune system. Following antigen encounter, B cells are activated, proliferate rapidly and undergo two diversification events; somatic hypermutation (followed by selection), which enhances the affinity of the antibody for its cognate antigen, and class-switch recombination, which alters the effector functions of the antibody to adapt the response to the challenge faced. B cells must then differentiate into antibody-secreting plasma cells or long-lived memory B cells. These activities take place in specialized immunological environments called germinal centres, usually located in the secondary lymphoid organs. To complete the germinal centre activities successfully, a B cell adopts a transcriptional programme that allows it to migrate to specific sites within the germinal centre, proliferate, modify its DNA recombination and repair pathways, alter its apoptotic potential and finally undergo terminal differentiation. To co-ordinate these processes, B cells employ a number of 'master regulator' transcription factors which mediate wholesale transcriptomic changes. These master transcription factors are mutually antagonistic and form a complex regulatory network to maintain distinct gene expression programs. Within this network, multiple points of positive and negative feedback ensure the expression of the 'master regulators', augmented by a number of 'secondary' factors that reinforce these networks and sense the progress of the immune response. In this review we will discuss the different activities B cells must undertake to mount a successful T cell-dependent immune response and describe how a regulatory network of transcription factors controls these processes.

  8. Transcriptional Network growing Models using Motif-based Preferential Attachment

    Directory of Open Access Journals (Sweden)

    Ahmed Farouk Abdelzaher

    2015-10-01

    Full Text Available Understanding relationships between architectural properties of gene-regulatory networks (GRNs has been one of the major goals in systems biology and bioinformatics, as it can provide insights into, e.g., disease dynamics and drug development. Such GRNs are characterized by their scale-free degree distributions and existence of network motifs--i.e., small-node subgraphs that occur more abundantly in GRNs than expected from chance alone. Because these transcriptional modules represent ``building blocks'' of complex networks and exhibit a wide range of functional and dynamical properties, they may contribute to the remarkable robustness and dynamical stability associated with the whole of GRNs. Here we developed network-construction models to better understand this relationship, which produce randomized GRNs by using transcriptional motifs as the fundamental growth unit in contrast to other methods that construct similar networks on a node-by-node basis. Because this model produces networks with a prescribed lower bound on the number of choice transcriptional motifs (e.g., downlinks, feed-forward loops, its fidelity to the motif distributions observed in model organisms represents an improvement over existing methods, which we validated by contrasting their resultant motif and degree distributions against existing network-growth models and data from the model organism of the bacterium Escherichia coli. These models may therefore serve as novel testbeds for further elucidating relationships between the topology of transcriptional motifs and network-wide dynamical properties.

  9. Transcriptional Network Growing Models Using Motif-Based Preferential Attachment.

    Science.gov (United States)

    Abdelzaher, Ahmed F; Al-Musawi, Ahmad F; Ghosh, Preetam; Mayo, Michael L; Perkins, Edward J

    2015-01-01

    Understanding relationships between architectural properties of gene-regulatory networks (GRNs) has been one of the major goals in systems biology and bioinformatics, as it can provide insights into, e.g., disease dynamics and drug development. Such GRNs are characterized by their scale-free degree distributions and existence of network motifs - i.e., small-node subgraphs that occur more abundantly in GRNs than expected from chance alone. Because these transcriptional modules represent "building blocks" of complex networks and exhibit a wide range of functional and dynamical properties, they may contribute to the remarkable robustness and dynamical stability associated with the whole of GRNs. Here, we developed network-construction models to better understand this relationship, which produce randomized GRNs by using transcriptional motifs as the fundamental growth unit in contrast to other methods that construct similar networks on a node-by-node basis. Because this model produces networks with a prescribed lower bound on the number of choice transcriptional motifs (e.g., downlinks, feed-forward loops), its fidelity to the motif distributions observed in model organisms represents an improvement over existing methods, which we validated by contrasting their resultant motif and degree distributions against existing network-growth models and data from the model organism of the bacterium Escherichia coli. These models may therefore serve as novel testbeds for further elucidating relationships between the topology of transcriptional motifs and network-wide dynamical properties.

  10. Spatial organization of transcription in bacterial cells.

    Science.gov (United States)

    Weng, Xiaoli; Xiao, Jie

    2014-07-01

    Prokaryotic transcription has been extensively studied over the past half a century. However, there often exists a gap between the structural, mechanistic description of transcription obtained from in vitro biochemical studies, and the cellular, phenomenological observations from in vivo genetic studies. It is now accepted that a living bacterial cell is a complex entity; the heterogeneous cellular environment is drastically different from the homogenous, well-mixed situation in vitro. Where molecules are inside a cell may be important for their function; hence, the spatial organization of different molecular components may provide a new means of transcription regulation in vivo, possibly bridging this gap. In this review, we survey current evidence for the spatial organization of four major components of transcription [genes, transcription factors, RNA polymerase (RNAP) and RNAs] and critically analyze their biological significance. Copyright © 2014 Elsevier Ltd. All rights reserved.

  11. ETS transcription factors in hematopoietic stem cell development.

    Science.gov (United States)

    Ciau-Uitz, Aldo; Wang, Lu; Patient, Roger; Liu, Feng

    2013-12-01

    Hematopoietic stem cells (HSCs) are essential for the maintenance of the hematopoietic system. However, these cells cannot be maintained or created in vitro, and very little is known about their generation during embryogenesis. Many transcription factors and signaling pathways play essential roles at various stages of HSC development. Members of the ETS ('E twenty-six') family of transcription factors are recognized as key regulators within the gene regulatory networks governing hematopoiesis, including the ontogeny of HSCs. Remarkably, although all ETS transcription factors bind the same DNA consensus sequence and overlapping tissue expression is observed, individual ETS transcription factors play unique roles in the development of HSCs. Also, these transcription factors are recurrently used throughout development and their functions are context-dependent, increasing the challenge of studying their mechanism of action. Critically, ETS factors also play roles under pathological conditions, such as leukemia and, therefore, deciphering their mechanism of action will not only enhance our knowledge of normal hematopoiesis, but also inform protocols for their creation in vitro from pluripotent stem cells and the design of new therapeutic approaches for the treatment of malignant blood cell diseases. In this review, we summarize the key findings on the roles of ETS transcription factors in HSC development and discuss novel mechanisms by which they could control hematopoiesis. © 2013.

  12. Post-transcriptional modifications in development and stem cells.

    Science.gov (United States)

    Frye, Michaela; Blanco, Sandra

    2016-11-01

    Cells adapt to their environment by linking external stimuli to an intricate network of transcriptional, post-transcriptional and translational processes. Among these, mechanisms that couple environmental cues to the regulation of protein translation are not well understood. Chemical modifications of RNA allow rapid cellular responses to external stimuli by modulating a wide range of fundamental biochemical properties and processes, including the stability, splicing and translation of messenger RNA. In this Review, we focus on the occurrence of N(6)-methyladenosine (m(6)A), 5-methylcytosine (m(5)C) and pseudouridine (Ψ) in RNA, and describe how these RNA modifications are implicated in regulating pluripotency, stem cell self-renewal and fate specification. Both post-transcriptional modifications and the enzymes that catalyse them modulate stem cell differentiation pathways and are essential for normal development. © 2016. Published by The Company of Biologists Ltd.

  13. Transcriptional Wiring of Cell Wall-Related Genes in Arabidopsis

    Institute of Scientific and Technical Information of China (English)

    Marek Mutwil; Colin Ruprecht; Federico M. Giorgi; Martin Bringmann; Bj(o)rn Usadel; Staffan Persson

    2009-01-01

    Transcriptional coordination, or co-expression, of genes may signify functional relatedness of the correspond-ing proteins. For example, several genes involved in secondary cell wall cellulose biosynthesis are co-expressed with genes engaged in the synthesis of xylan, which is a major component of the secondary cell wall. To extend these types of anal-yses, we investigated the co-expression relationships of all Carbohydrate-Active enZYmes (CAZy)-related genes for Arabidopsis thaliana. Thus, the intention was to transcriptionally link different cell wall-related processes to each other, and also to other biological functions. To facilitate easy manual inspection, we have displayed these interactions as networks and matrices, and created a web-based interface (http://aranet.mpimp-golm.mpg.de/corecarb) containing downloadable files for all the transcriptional associations.

  14. Biophysical models of transcription in cells

    Science.gov (United States)

    Choubey, Sandeep

    Cells constantly face environmental challenges and deal with them by changing their gene expression patterns. They make decisions regarding which genes to express and which genes not to express based on intra-cellular and environmental cues. These decisions are often made by regulating the process of transcription. While the identities of the different molecules that take part in regulating transcription have been determined for a number of different genes, their dynamics inside the cell are still poorly understood. One key feature of these regulatory dynamics is that the numbers of the bio-molecules involved is typically small, resulting in large temporal fluctuations in transcriptional outputs (mRNA and protein). In this thesis I show that measurements of the cell-to-cell variability of the distribution of transcribing RNA polymerases along a gene provide a previously unexplored method for deciphering the mechanism of its transcription in vivo. First, I propose a simple kinetic model of transcription initiation and elongation from which I calculate transcribing RNA polymerase copy-number fluctuations. I test my theory against published data obtained for yeast genes and propose a novel mechanism of transcription. Rather than transcription being initiated through a single rate-limiting step, as was previously proposed, my single-cell analysis reveals the presence of at least two rate limiting steps. Second, I compute the distribution of inter-polymerase distance distribution along a gene and propose a method for analyzing inter-polymerase distance distributions acquired in experiments. By applying this method to images of polymerases transcribing ribosomal genes in E.coli I show that one model of regulation of these genes is consistent with inter-polymerase distance data while a number of other models are not. The analytical framework described in this thesis can be used to extract quantitative information about the dynamics of transcription from single-cell

  15. HIV transcription is induced in dying cells

    Energy Technology Data Exchange (ETDEWEB)

    Woloschak, G.E.; Chang-Liu, Chin-Mei [Argonne National Lab., IL (United States); Schreck, S. [Argonne National Lab., IL (United States)]|[Univ. of South Carolina, Columbia, SC (United States). Dept. of Chemistry; Panozzo, J. [Loyola Univ. Medical Center, Maywood, IL (United States); Libertin, C.R. [Loyola Univ. Medical Center, Maywood, IL (United States)

    1996-02-01

    Using HeLa cells stably transfected with an HIV-LTR-CAT construct, we demonstrated a peak in CAT induction that occurs in viable (but not necessarily cell-division-competent) cells 24 h following exposure to some cell-killing agents. {gamma} rays were the only cell-killing agent which did not induce HIV transcription; this can be attributed to the fact that {gamma}-ray-induced apoptotic death requires functional p53, which is not present in HeLa cells. For all other agents, HIV-LTR induction was dose-dependent and correlated with the amount of cell killing that occurred in the culture. Doses which caused over 99% cell killing induced HIV-LTR transcription maximally, demonstrating that cells that will go on to die by 14 days are the cells expressing HIV-LTR-CAT.

  16. Motif Participation by Genes in E. coli Transcriptional Networks

    Directory of Open Access Journals (Sweden)

    Michael eMayo

    2012-09-01

    Full Text Available Motifs are patterns of recurring connections among the genes of genetic networks that occur more frequently than would be expected from randomized networks with the same degree sequence. Although the abundance of certain three-node motifs, such as the feed-forward loop, is positively correlated with a networks’ ability to tolerate moderate disruptions to gene expression, little is known regarding the connectivity of individual genes participating in multiple motifs. Using the transcriptional network of the bacterium Escherichia coli, we investigate this feature by reconstructing the distribution of genes participating in feed-forward loop motifs from its largest connected network component. We contrast these motif participation distributions with those obtained from model networks built using the preferential attachment mechanism employed by many biological and man-made networks. We report that, although some of these model networks support a motif participation distribution that appears qualitatively similar to that obtained from the bacterium Escherichia coli, the probability for a node to support a feed-forward loop motif may instead be strongly influenced by only a few master transcriptional regulators within the network. From these analyses we conclude that such master regulators may be a crucial ingredient to describe coupling among feed-forward loop motifs in transcriptional regulatory networks.

  17. Model transcriptional networks with continuously varying expression levels

    Directory of Open Access Journals (Sweden)

    Carneiro Mauricio O

    2011-12-01

    Full Text Available Abstract Background At a time when genomes are being sequenced by the hundreds, much attention has shifted from identifying genes and phenotypes to understanding the networks of interactions among genes. We developed a gene network developmental model expanding on previous models of transcription regulatory networks. In our model, each network is described by a matrix representing the interactions between transcription factors, and a vector of continuous values representing the transcription factor expression in an individual. Results In this work we used the gene network model to look at the impact of mating as well as insertions and deletions of genes in the evolution of complexity of these networks. We found that the natural process of diploid mating increases the likelihood of maintaining complexity, especially in higher order networks (more than 10 genes. We also show that gene insertion is a very efficient way to add more genes to a network as it provides a much higher chance of developmental stability. Conclusions The continuous model affords a more complete view of the evolution of interacting genes. The notion of a continuous output vector also incorporates the reality of gene networks and graded concentrations of gene products.

  18. Dissection of the oncogenic MYCN transcriptional network reveals a large set of clinically relevant cell cycle genes as drivers of neuroblastoma tumorigenesis.

    Science.gov (United States)

    Murphy, Derek M; Buckley, Patrick G; Bryan, Kenneth; Watters, Karen M; Koster, Jan; van Sluis, Peter; Molenaar, Jan; Versteeg, Rogier; Stallings, Raymond L

    2011-06-01

    Amplification of the oncogenic transcription factor MYCN plays a major role in the pathogenesis of several pediatric cancers, including neuroblastoma, medulloblastoma, and rhabodomyosarcoma. For neuroblastoma, MYCN amplification is the most powerful genetic predictor of poor patient survival, yet the mechanism by which MYCN drives tumorigenesis is only partially understood. To gain an insight into the distribution of MYCN binding and to identify clinically relevant MYCN target genes, we performed an integrated analysis of MYCN ChIP-chip and mRNA expression using the MYCN repressible SHEP-21N neuroblastoma cell line. We hypothesized that genes exclusively MYCN bound in SHEP-21N cells over-expressing MYCN would be enriched for direct targets which contribute to the process of disease progression. Integrated analysis revealed that MYCN drives tumorigenesis predominantly as a positive regulator of target gene transcription. A high proportion of genes (24%) that are MYCN bound and up-regulated in the SHEP-21N model are significantly associated with poor overall patient survival (OS) in a set of 88 tumors. In contrast, the proportion of genes down-regulated when bound by MYCN in the SHEP-21N model and which are significantly associated with poor overall patient survival when under-expressed in primary tumors was significantly lower (5%). Gene ontology analysis determined a highly statistically significant enrichment for cell cycle related genes within the over-expressed MYCN target group which were also associated with poor OS. We conclude that the over-expression of MYCN leads to aberrant binding and over-expression of genes associated with cell cycle regulation which are significantly correlated with poor OS and MYCN amplification.

  19. Transcriptional networks for alcohol sensitivity in Drosophila melanogaster.

    Science.gov (United States)

    Morozova, Tatiana V; Mackay, Trudy F C; Anholt, Robert R H

    2011-04-01

    Understanding the genetic architecture of polygenic traits requires investigating how complex networks of interacting molecules mediate the effect of genetic variation on organismal phenotypes. We used a combination of P-element mutagenesis and analysis of natural variation in gene expression to predict transcriptional networks that underlie alcohol sensitivity in Drosophila melanogaster. We identified 139 unique P-element mutations (124 in genes) that affect sensitivity or resistance to alcohol exposure. Further analyses of nine of the lines showed that the P-elements affected expression levels of the tagged genes, and P-element excision resulted in phenotypic reversion. The majority of the mutations were in computationally predicted genes or genes with unexpected effects on alcohol phenotypes. Therefore we sought to understand the biological relationships among 21 of these genes by leveraging genetic correlations among genetically variable transcripts in wild-derived inbred lines to predict coregulated transcriptional networks. A total of 32 "hub" genes were common to two or more networks associated with the focal genes. We used RNAi-mediated inhibition of expression of focal genes and of hub genes connected to them in the network to confirm their effects on alcohol-related phenotypes. We then expanded the computational networks using the hub genes as foci and again validated network predictions. Iteration of this approach allows a stepwise expansion of the network with simultaneous functional validation. Although coregulated transcriptional networks do not provide information about causal relationships among their constituent transcripts, they provide a framework for subsequent functional studies on the genetic basis of alcohol sensitivity.

  20. A core erythroid transcriptional network is repressed by a master regulator of myelo-lymphoid differentiation.

    Science.gov (United States)

    Wontakal, Sandeep N; Guo, Xingyi; Smith, Cameron; MacCarthy, Thomas; Bresnick, Emery H; Bergman, Aviv; Snyder, Michael P; Weissman, Sherman M; Zheng, Deyou; Skoultchi, Arthur I

    2012-03-06

    Two mechanisms that play important roles in cell fate decisions are control of a "core transcriptional network" and repression of alternative transcriptional programs by antagonizing transcription factors. Whether these two mechanisms operate together is not known. Here we report that GATA-1, SCL, and Klf1 form an erythroid core transcriptional network by co-occupying >300 genes. Importantly, we find that PU.1, a negative regulator of terminal erythroid differentiation, is a highly integrated component of this network. GATA-1, SCL, and Klf1 act to promote, whereas PU.1 represses expression of many of the core network genes. PU.1 also represses the genes encoding GATA-1, SCL, Klf1, and important GATA-1 cofactors. Conversely, in addition to repressing PU.1 expression, GATA-1 also binds to and represses >100 PU.1 myelo-lymphoid gene targets in erythroid progenitors. Mathematical modeling further supports that this dual mechanism of repressing both the opposing upstream activator and its downstream targets provides a synergistic, robust mechanism for lineage specification. Taken together, these results amalgamate two key developmental principles, namely, regulation of a core transcriptional network and repression of an alternative transcriptional program, thereby enhancing our understanding of the mechanisms that establish cellular identity.

  1. Deciphering the transcriptional-regulatory network of flocculation in Schizosaccharomyces pombe.

    Science.gov (United States)

    Kwon, Eun-Joo Gina; Laderoute, Amy; Chatfield-Reed, Kate; Vachon, Lianne; Karagiannis, Jim; Chua, Gordon

    2012-01-01

    In the fission yeast Schizosaccharomyces pombe, the transcriptional-regulatory network that governs flocculation remains poorly understood. Here, we systematically screened an array of transcription factor deletion and overexpression strains for flocculation and performed microarray expression profiling and ChIP-chip analysis to identify the flocculin target genes. We identified five transcription factors that displayed novel roles in the activation or inhibition of flocculation (Rfl1, Adn2, Adn3, Sre2, and Yox1), in addition to the previously-known Mbx2, Cbf11, and Cbf12 regulators. Overexpression of mbx2(+) and deletion of rfl1(+) resulted in strong flocculation and transcriptional upregulation of gsf2(+)/pfl1(+) and several other putative flocculin genes (pfl2(+)-pfl9(+)). Overexpression of the pfl(+) genes singly was sufficient to trigger flocculation, and enhanced flocculation was observed in several combinations of double pfl(+) overexpression. Among the pfl1(+) genes, only loss of gsf2(+) abrogated the flocculent phenotype of all the transcription factor mutants and prevented flocculation when cells were grown in inducing medium containing glycerol and ethanol as the carbon source, thereby indicating that Gsf2 is the dominant flocculin. In contrast, the mild flocculation of adn2(+) or adn3(+) overexpression was likely mediated by the transcriptional activation of cell wall-remodeling genes including gas2(+), psu1(+), and SPAC4H3.03c. We also discovered that Mbx2 and Cbf12 displayed transcriptional autoregulation, and Rfl1 repressed gsf2(+) expression in an inhibitory feed-forward loop involving mbx2(+). These results reveal that flocculation in S. pombe is regulated by a complex network of multiple transcription factors and target genes encoding flocculins and cell wall-remodeling enzymes. Moreover, comparisons between the flocculation transcriptional-regulatory networks of Saccharomyces cerevisiae and S. pombe indicate substantial rewiring of transcription

  2. Evolution of transcriptional networks in yeast: alternative teams of transcriptional factors for different species

    OpenAIRE

    Adriana Muñoz; Daniella Santos Muñoz; Aleksey Zimin; Yorke, James A.

    2016-01-01

    Background The diversity in eukaryotic life reflects a diversity in regulatory pathways. Nocedal and Johnson argue that the rewiring of gene regulatory networks is a major force for the diversity of life, that changes in regulation can create new species. Results We have created a method (based on our new “ping-pong algorithm) for detecting more complicated rewirings, where several transcription factors can substitute for one or more transcription factors in the regulation of a family of co-r...

  3. A developmental transcriptional network for maize defines coexpression modules.

    Science.gov (United States)

    Downs, Gregory S; Bi, Yong-Mei; Colasanti, Joseph; Wu, Wenqing; Chen, Xi; Zhu, Tong; Rothstein, Steven J; Lukens, Lewis N

    2013-04-01

    Here, we present a genome-wide overview of transcriptional circuits in the agriculturally significant crop species maize (Zea mays). We examined transcript abundance data at 50 developmental stages, from embryogenesis to senescence, for 34,876 gene models and classified genes into 24 robust coexpression modules. Modules were strongly associated with tissue types and related biological processes. Sixteen of the 24 modules (67%) have preferential transcript abundance within specific tissues. One-third of modules had an absence of gene expression in specific tissues. Genes within a number of modules also correlated with the developmental age of tissues. Coexpression of genes is likely due to transcriptional control. For a number of modules, key genes involved in transcriptional control have expression profiles that mimic the expression profiles of module genes, although the expression of transcriptional control genes is not unusually representative of module gene expression. Known regulatory motifs are enriched in several modules. Finally, of the 13 network modules with more than 200 genes, three contain genes that are notably clustered (P < 0.05) within the genome. This work, based on a carefully selected set of major tissues representing diverse stages of maize development, demonstrates the remarkable power of transcript-level coexpression networks to identify underlying biological processes and their molecular components.

  4. Global analysis of photosynthesis transcriptional regulatory networks.

    Science.gov (United States)

    Imam, Saheed; Noguera, Daniel R; Donohue, Timothy J

    2014-12-01

    Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

  5. Protein modularity, cooperative binding, and hybrid regulatory states underlie transcriptional network diversification.

    Science.gov (United States)

    Baker, Christopher R; Booth, Lauren N; Sorrells, Trevor R; Johnson, Alexander D

    2012-09-28

    We examine how different transcriptional network structures can evolve from an ancestral network. By characterizing how the ancestral mode of gene regulation for genes specific to a-type cells in yeast species evolved from an activating paradigm to a repressing one, we show that regulatory protein modularity, conversion of one cis-regulatory sequence to another, distribution of binding energy among protein-protein and protein-DNA interactions, and exploitation of ancestral network features all contribute to the evolution of a novel regulatory mode. The formation of this derived mode of regulation did not disrupt the ancestral mode and thereby created a hybrid regulatory state where both means of transcription regulation (ancestral and derived) contribute to the conserved expression pattern of the network. Finally, we show how this hybrid regulatory state has resolved in different ways in different lineages to generate the diversity of regulatory network structures observed in modern species.

  6. Transcriptional networks implicated in human nonalcoholic fatty liver disease.

    Science.gov (United States)

    Ye, Hua; Liu, Wei

    2015-10-01

    The transcriptome of nonalcoholic fatty liver disease (NAFLD) was investigated in several studies. However, the implications of transcriptional networks in progressive NAFLD are not clear and mechanisms inducing transition from nonalcoholic simple fatty liver (NAFL) to nonalcoholic steatohepatitis (NASH) are still elusive. The aims of this study were to (1) construct networks for progressive NAFLD, (2) identify hub genes and functional modules in these networks and (3) infer potential linkages among hub genes, transcription factors and microRNAs (miRNA) for NAFLD progression. A systems biology approach by combining differential expression analysis and weighted gene co-expression network analysis (WGCNA) was utilized to dissect transcriptional profiles in 19 normal, 10 NAFL and 16 NASH patients. Based on this framework, 3 modules related to chromosome organization, proteasomal ubiquitin-dependent protein degradation and immune response were identified in NASH network. Furthermore, 9 modules of co-expressed genes associated with NAFL/NASH transition were found. Further characterization of these modules defined 13 highly connected hub genes in NAFLD progression network. Interestingly, 11 significantly changed miRNAs were predicted to target 10 of the 13 hub genes. Characterization of modules and hub genes that may be regulated by miRNAs could facilitate the identification of candidate genes and pathways responsible for NAFL/NASH transition and lead to a better understanding of NAFLD pathogenesis. The identified modules and hub genes may point to potential targets for therapeutic interventions.

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

    Science.gov (United States)

    Heath, Allison; Kavraki, Lydia; Balázsi, Gábor

    2008-03-01

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

  8. A transcriptional network underlies susceptibility to kidney disease progression.

    Science.gov (United States)

    Laouari, Denise; Burtin, Martine; Phelep, Aurélie; Bienaime, Frank; Noel, Laure-Hélène; Lee, David C; Legendre, Christophe; Friedlander, Gérard; Pontoglio, Marco; Terzi, Fabiola

    2012-08-01

    The molecular networks that control the progression of chronic kidney diseases (CKD) are poorly defined. We have recently shown that the susceptibility to development of renal lesions after nephron reduction is controlled by a locus on mouse chromosome 6 and requires epidermal growth factor receptor (EGFR) activation. Here, we identified microphthalmia-associated transcription factor A (MITF-A), a bHLH-Zip transcription factor, as a modifier of CKD progression. Sequence analysis revealed a strain-specific mutation in the 5' UTR that decreases MITF-A protein synthesis in lesion-prone friend virus B NIH (FVB/N) mice. More importantly, we dissected the molecular pathway by which MITF-A modulates CKD progression. MITF-A interacts with histone deacetylases to repress the transcription of TGF-α, a ligand of EGFR, and antagonizes transactivation by its related partner, transcription factor E3 (TFE3). Consistent with the key role of this network in CKD, Tgfa gene inactivation protected FVB/N mice from renal deterioration after nephron reduction. These data are relevant to human CKD, as we found that the TFE3/MITF-A ratio was increased in patients with damaged kidneys. Our study uncovers a novel transcriptional network and unveils novel potential prognostic and therapeutic targets for preventing human CKD progression.

  9. Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response.

    Science.gov (United States)

    Manioudaki, Maria E; Poirazi, Panayiota

    2013-01-01

    Over the last decade, numerous computational methods have been developed in order to infer and model biological networks. Transcriptional networks in particular have attracted significant attention due to their critical role in cell survival. The majority of network inference methods use genome-wide experimental data to search for modules of genes with coherent expression profiles and common regulators, often ignoring the multi-layer structure of transcriptional cascades. Modeling methodologies on the other hand assume a given network structure and vary significantly in their algorithmic approach, ranging from over-simplified representations (e.g., Boolean networks) to detailed -but computationally expensive-network simulations (e.g., with differential equations). In this work we use Artificial Neural Networks (ANNs) to model transcriptional regulatory cascades that emerge during the stress response in Saccharomyces cerevisiae and extend in three layers. We confine the structure of the ANNs to match the structure of the biological networks as determined by gene expression, DNA-protein interaction and experimental evidence provided in publicly available databases. Trained ANNs are able to predict the expression profile of 11 target genes across multiple experimental conditions with a correlation coefficient >0.7. When time-dependent interactions between upstream transcription factors (TFs) and their indirect targets are also included in the ANNs, accurate predictions are achieved for 30/34 target genes. Moreover, heterodimer formation is taken into account. We show that ANNs can be used to (1) accurately predict the expression of downstream genes in a 3-layer transcriptional cascade based on the expression of their indirect regulators and (2) infer the condition- and time-dependent activity of various TFs as well as during heterodimer formation. We show that a three-layer regulatory cascade whose structure is determined by co-expressed gene modules and their

  10. Transcription factor interplay in T helper cell differentiation.

    Science.gov (United States)

    Evans, Catherine M; Jenner, Richard G

    2013-11-01

    The differentiation of CD4 helper T cells into specialized effector lineages has provided a powerful model for understanding immune cell differentiation. Distinct lineages have been defined by differential expression of signature cytokines and the lineage-specifying transcription factors necessary and sufficient for their production. The traditional paradigm of differentiation towards Th1 and Th2 subtypes driven by T-bet and GATA3, respectively, has been extended to incorporate additional T cell lineages and transcriptional regulators. Technological advances have expanded our view of these lineage-specifying transcription factors to the whole genome and revealed unexpected interplay between them. From these data, it is becoming clear that lineage specification is more complex and plastic than previous models might have suggested. Here, we present an overview of the different forms of transcription factor interplay that have been identified and how T cell phenotypes arise as a product of this interplay within complex regulatory networks. We also suggest experimental strategies that will provide further insight into the mechanisms that underlie T cell lineage specification and plasticity.

  11. Transcriptional network of p63 in human keratinocytes.

    Directory of Open Access Journals (Sweden)

    Silvia Pozzi

    Full Text Available p63 is a transcription factor required for the development and maintenance of ectodermal tissues in general, and skin keratinocytes in particular. The identification of its target genes is fundamental for understanding the complex network of gene regulation governing the development of epithelia. We report a list of almost 1000 targets derived from ChIP on chip analysis on two platforms; all genes analyzed changed in expression during differentiation of human keratinocytes. Functional annotation highlighted unexpected GO terms enrichments and confirmed that genes involved in transcriptional regulation are the most significant. A detailed analysis of these transcriptional regulators in condition of perturbed p63 levels confirmed the role of p63 in the regulatory network. Rather than a rigid master-slave hierarchical model, our data indicate that p63 connects different hubs involved in the multiple specific functions of the skin.

  12. Modelling transcriptional networks in leaf senescence.

    Science.gov (United States)

    Penfold, Christopher A; Buchanan-Wollaston, Vicky

    2014-07-01

    The process of leaf senescence is induced by an extensive range of developmental and environmental signals and controlled by multiple, cross-linking pathways, many of which overlap with plant stress-response signals. Elucidation of this complex regulation requires a step beyond a traditional one-gene-at-a-time analysis. Application of a more global analysis using statistical and mathematical tools of systems biology is an approach that is being applied to address this problem. A variety of modelling methods applicable to the analysis of current and future senescence data are reviewed and discussed using some senescence-specific examples. Network modelling with a senescence transcriptome time course followed by testing predictions with gene-expression data illustrates the application of systems biology tools.

  13. Iterative reconstruction of transcriptional regulatory networks: an algorithmic approach.

    Directory of Open Access Journals (Sweden)

    Christian L Barrett

    2006-05-01

    Full Text Available The number of complete, publicly available genome sequences is now greater than 200, and this number is expected to rapidly grow in the near future as metagenomic and environmental sequencing efforts escalate and the cost of sequencing drops. In order to make use of this data for understanding particular organisms and for discerning general principles about how organisms function, it will be necessary to reconstruct their various biochemical reaction networks. Principal among these will be transcriptional regulatory networks. Given the physical and logical complexity of these networks, the various sources of (often noisy data that can be utilized for their elucidation, the monetary costs involved, and the huge number of potential experiments approximately 10(12 that can be performed, experiment design algorithms will be necessary for synthesizing the various computational and experimental data to maximize the efficiency of regulatory network reconstruction. This paper presents an algorithm for experimental design to systematically and efficiently reconstruct transcriptional regulatory networks. It is meant to be applied iteratively in conjunction with an experimental laboratory component. The algorithm is presented here in the context of reconstructing transcriptional regulation for metabolism in Escherichia coli, and, through a retrospective analysis with previously performed experiments, we show that the produced experiment designs conform to how a human would design experiments. The algorithm is able to utilize probability estimates based on a wide range of computational and experimental sources to suggest experiments with the highest potential of discovering the greatest amount of new regulatory knowledge.

  14. Complexity of the transcriptional network controlling secondary wall biosynthesis.

    Science.gov (United States)

    Zhong, Ruiqin; Ye, Zheng-Hua

    2014-12-01

    Secondary walls in the form of wood and fibers are the most abundant biomass produced by vascular plants, and are important raw materials for many industrial uses. Understanding how secondary walls are constructed is of significance in basic plant biology and also has far-reaching implications in genetic engineering of plant biomass better suited for various end uses, such as biofuel production. Secondary walls are composed of three major biopolymers, i.e., cellulose, hemicelluloses and lignin, the biosynthesis of which requires the coordinated transcriptional regulation of all their biosynthesis genes. Genomic and molecular studies have identified a number of transcription factors, whose expression is associated with secondary wall biosynthesis. We comprehensively review how these secondary wall-associated transcription factors function together to turn on the secondary wall biosynthetic program, which leads to secondary wall deposition in vascular plants. The transcriptional network regulating secondary wall biosynthesis employs a multi-leveled feed-forward loop regulatory structure, in which the top-level secondary wall NAC (NAM, ATAF1/2 and CUC2) master switches activate the second-level MYB master switches and they together induce the expression of downstream transcription factors and secondary wall biosynthesis genes. Secondary wall NAC master switches and secondary wall MYB master switches bind to and activate the SNBE (secondary wall NAC binding element) and SMRE (secondary wall MYB-responsive element) sites, respectively, in their target gene promoters. Further investigation of what and how developmental signals trigger the transcriptional network to regulate secondary wall biosynthesis and how different secondary wall-associated transcription factors function cooperatively in activating secondary wall biosynthetic pathways will lead to a better understanding of the molecular mechanisms underlying the transcriptional control of secondary wall biosynthesis.

  15. Transcriptional control in the segmentation gene network of Drosophila.

    Directory of Open Access Journals (Sweden)

    Mark D Schroeder

    2004-09-01

    Full Text Available The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross- regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a

  16. Metabolic constraint-based refinement of transcriptional regulatory networks.

    Science.gov (United States)

    Chandrasekaran, Sriram; Price, Nathan D

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10(-172)), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10(-14)) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework to

  17. Cross-species transcriptional network analysis defines shared inflammatory responses in murine and human lupus nephritis.

    Science.gov (United States)

    Berthier, Celine C; Bethunaickan, Ramalingam; Gonzalez-Rivera, Tania; Nair, Viji; Ramanujam, Meera; Zhang, Weijia; Bottinger, Erwin P; Segerer, Stephan; Lindenmeyer, Maja; Cohen, Clemens D; Davidson, Anne; Kretzler, Matthias

    2012-07-15

    Lupus nephritis (LN) is a serious manifestation of systemic lupus erythematosus. Therapeutic studies in mouse LN models do not always predict outcomes of human therapeutic trials, raising concerns about the human relevance of these preclinical models. In this study, we used an unbiased transcriptional network approach to define, in molecular terms, similarities and differences among three lupus models and human LN. Genome-wide gene-expression networks were generated using natural language processing and automated promoter analysis and compared across species via suboptimal graph matching. The three murine models and human LN share both common and unique features. The 20 commonly shared network nodes reflect the key pathologic processes of immune cell infiltration/activation, endothelial cell activation/injury, and tissue remodeling/fibrosis, with macrophage/dendritic cell activation as a dominant cross-species shared transcriptional pathway. The unique nodes reflect differences in numbers and types of infiltrating cells and degree of remodeling among the three mouse strains. To define mononuclear phagocyte-derived pathways in human LN, gene sets activated in isolated NZB/W renal mononuclear cells were compared with human LN kidney profiles. A tissue compartment-specific macrophage-activation pattern was seen, with NF-κB1 and PPARγ as major regulatory nodes in the tubulointerstitial and glomerular networks, respectively. Our study defines which pathologic processes in murine models of LN recapitulate the key transcriptional processes active in human LN and suggests that there are functional differences between mononuclear phagocytes infiltrating different renal microenvironments.

  18. Structure and properties of transcriptional networks driving selenite stress response in yeasts

    Directory of Open Access Journals (Sweden)

    Lelandais Gaelle

    2008-07-01

    Full Text Available Abstract Background Stress responses provide valuable models for deciphering the transcriptional networks controlling the adaptation of the cell to its environment. We analyzed the transcriptome response of yeast to toxic concentrations of selenite. We used gene network mapping tools to identify functional pathways and transcription factors involved in this response. We then used chromatin immunoprecipitation and knock-out experiments to investigate the role of some of these regulators and the regulatory connections between them. Results Selenite rapidly activates a battery of transcriptional circuits, including iron deprivation, oxidative stress and protein degradation responses. The mRNA levels of several transcriptional regulators are themselves regulated. We demonstrate the existence of a positive transcriptional loop connecting the regulator of proteasome expression, Rpn4p, to the pleiotropic drug response factor, Pdr1p. We also provide evidence for the involvement of this regulatory module in the oxidative stress response controlled by the Yap1p transcription factor and its conservation in the pathogenic yeast C. glabrata. In addition, we show that the drug resistance regulator gene YRR1 and the iron homeostasis regulator gene AFT2 are both directly regulated by Yap1p. Conclusion This work depicted a highly interconnected and complex transcriptional network involved in the adaptation of yeast genome expression to the presence of selenite in its chemical environment. It revealed the transcriptional regulation of PDR1 by Rpn4p, proposed a new role for the pleiotropic drug resistance network in stress response and demonstrated a direct regulatory connection between oxidative stress response and iron homeostasis.

  19. Transcriptional regulation of the carbohydrate utilization network in Thermotoga maritima

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    Dmitry A Rodionov

    2013-08-01

    Full Text Available Hyperthermophilic bacteria from the Thermotogales lineage can produce hydrogen by fermenting a wide range of carbohydrates. Previous experimental studies identified a large fraction of genes committed to carbohydrate degradation and utilization in the model bacterium Thermotoga maritima. Knowledge of these genes enabled comprehensive reconstruction of biochemical pathways comprising the carbohydrate utilization network. However, transcriptional factors (TFs and regulatory mechanisms driving this network remained largely unknown. Here, we used an integrated approach based on comparative analysis of genomic and transcriptomic data for the reconstruction of the carbohydrate utilization regulatory networks in 11 Thermotogales genomes. We identified DNA-binding motifs and regulons for 19 orthologous TFs in the Thermotogales. The inferred regulatory network in T. maritima contains 181 genes encoding TFs, sugar catabolic enzymes and ABC-family transporters. In contrast to many previously described bacteria, a transcriptional regulation strategy of Thermotoga does not employ global regulatory factors. The reconstructed regulatory network in T. maritima was validated by gene expression profiling on a panel of mono- and disaccharides and by in vitro DNA-binding assays. The observed upregulation of genes involved in catabolism of pectin, trehalose, cellobiose, arabinose, rhamnose, xylose, glucose, galactose, and ribose showed a strong correlation with the UxaR, TreR, BglR, CelR, AraR, RhaR, XylR, GluR, GalR, and RbsR regulons. Ultimately, this study elucidated the transcriptional regulatory network and mechanisms controlling expression of carbohydrate utilization genes in T. maritima. In addition to improving the functional annotations of associated transporters and catabolic enzymes, this research provides novel insights into the evolution of regulatory networks in Thermotogales.

  20. Deciphering the Innate Lymphoid Cell Transcriptional Program

    Directory of Open Access Journals (Sweden)

    Cyril Seillet

    2016-10-01

    Full Text Available Innate lymphoid cells (ILCs are enriched at mucosal surfaces, where they provide immune surveillance. All ILC subsets develop from a common progenitor that gives rise to pre-committed progenitors for each of the ILC lineages. Currently, the temporal control of gene expression that guides the emergence of these progenitors is poorly understood. We used global transcriptional mapping to analyze gene expression in different ILC progenitors. We identified PD-1 to be specifically expressed in PLZF+ ILCp and revealed that the timing and order of expression of the transcription factors NFIL3, ID2, and TCF-1 was critical. Importantly, induction of ILC lineage commitment required only transient expression of NFIL3 prior to ID2 and TCF-1 expression. These findings highlight the importance of the temporal program that permits commitment of progenitors to the ILC lineage, and they expand our understanding of the core transcriptional program by identifying potential regulators of ILC development.

  1. Dissection of the Oncogenic MYCN Transcriptional Network Reveals a Large Set of Clinically Relevant Cell Cycle Genes as Drivers of Neuroblastoma Tumorigenesis

    NARCIS (Netherlands)

    D.M. Murphy; P.G. Buckley; K. Bryan; K.M. Watters; J. Koster; P. van Sluis; J. Molenaar; R. Versteeg; R.L. Stallings

    2011-01-01

    Amplification of the oncogenic transcription factor MYCN plays a major role in the pathogenesis of several pediatric cancers, including neuroblastoma, medulloblastoma, and rhabodomyosarcoma. For neuroblastoma, MYCN amplification is the most powerful genetic predictor of poor patient survival, yet th

  2. Isolated guitar transcription using a deep belief network

    Directory of Open Access Journals (Sweden)

    Gregory Burlet

    2017-03-01

    Full Text Available Music transcription involves the transformation of an audio recording to common music notation, colloquially referred to as sheet music. Manually transcribing audio recordings is a difficult and time-consuming process, even for experienced musicians. In response, several algorithms have been proposed to automatically analyze and transcribe the notes sounding in an audio recording; however, these algorithms are often general-purpose, attempting to process any number of instruments producing any number of notes sounding simultaneously. This paper presents a polyphonic transcription algorithm that is constrained to processing the audio output of a single instrument, specifically an acoustic guitar. The transcription system consists of a novel note pitch estimation algorithm that uses a deep belief network and multi-label learning techniques to generate multiple pitch estimates for each analysis frame of the input audio signal. Using a compiled dataset of synthesized guitar recordings for evaluation, the algorithm described in this work results in an 11% increase in the f-measure of note transcriptions relative to Zhou et al.’s (2009 transcription algorithm in the literature. This paper demonstrates the effectiveness of deep, multi-label learning for the task of polyphonic transcription.

  3. Topological peculiarities of mammalian networks with different functionalities: transcription, signal transduction and metabolic networks

    Directory of Open Access Journals (Sweden)

    Bjorn Goemann

    2011-12-01

    Full Text Available We have comparatively investigated three different mammalian networks - on transcription, signal transduction and metabolic processes - with respect to their common and individual topological traits. The networks have been constructed based on genome- wide data collected from human, mouse and rat. None of these three networks exhibits a pure power-law degree distribution and, therefore, could be considered scalefree. Rather, the degree distributions of all three networks were best fitted by mixed models of a power law with an exponential tail. The networks differ from one another in the quantitative parameters of the models. Moreover, the transcription network can also be very well approximated by an exponential law. The connectivity within each network is rather robust, as is seen when removing individual nodes and computing the values of their pairwise disconnectivity index (PDI, which characterizes the topological significance of each node v by the number of direct or indirect connections in the network that critically depend on the presence of v. The results evidence that the networks are not centralized: none of nodes globally controls the integrity of each network. Just a few vertices appeared to strongly affect the coherence of the networks. These nodes are characterized by a broad range of degrees, thereby indicating that the degree alone is not the decisive criteria of a node's importance. The networks reveal distinct architectures: The transcriptional network exhibits a hierarchical modularity, whereas the signaling network is mainly comprised of semi-autonomous modules. The metabolic network seems to be made by a more complex mixture of substructures. Thus, despite being encoded by the same genomes, the networks significantly differ from one another in their general architectural design. Altogether, our results indicate that the subsets of genes and relationships that constitute these networks have co-evolved very differently and

  4. HIV transcription is induced in dying cells

    Energy Technology Data Exchange (ETDEWEB)

    Woloschak, G.E.; Chang-Liu, Chin-Mei [Argonne National Lab., IL (United States); Schreck, S. [Argonne National Lab., IL (United States)]|[Univ. of South Carolina, Columbia, SC (United States). Dept. of Chemistry

    1995-06-01

    Using HeLa cells stably transfected with an HIV-LTR-CAT construct, we demonstrated a peak in CAT induction that occurs in viable (but not necessarily cell-division-competent) cells 24 h following exposure to some cell-killing agents. {gamma} rays were the only cell-killing agent which did not induce HIV transcription; this can be attributed to the fact that {gamma}-ray-induced apoptotic death requires functional p53, which is not present in HeLa cells. For all other agents, HIV-LTR induction was dose-dependent and correlated with the amount of cell killing that occurred in the culture. 14 refs., 4 figs., 1 tab.

  5. Gfi1 and gfi1b repress rag transcription in plasmacytoid dendritic cells in vitro.

    Directory of Open Access Journals (Sweden)

    Kwan T Chow

    Full Text Available Growth factor independence genes (Gfi1 and Gfi1b repress recombination activating genes (Rag transcription in developing B lymphocytes. Because all blood lineages originate from hematopoietic stem cells (HSCs and different lineage progenitors have been shown to share transcription factor networks prior to cell fate commitment, we hypothesized that GFI family proteins may also play a role in repressing Rag transcription or a global lymphoid transcriptional program in other blood lineages. We tested the level of Rag transcription in various blood cells when Gfi1 and Gfi1b were deleted, and observed an upregulation of Rag expression in plasmacytoid dendritic cells (pDCs. Using microarray analysis, we observed that Gfi1 and Gfi1b do not regulate a lymphoid or pDC-specific transcriptional program. This study establishes a role for Gfi1 and Gfi1b in Rag regulation in a non-B lineage cell type.

  6. Roadmap to cellular reprogramming--manipulating transcriptional networks with DNA, RNA, proteins and small molecules.

    Science.gov (United States)

    Wörsdörfer, P; Thier, M; Kadari, A; Edenhofer, F

    2013-06-01

    Recent reports demonstrate that the plasticity of mammalian somatic cells is much higher than previously assumed and that ectopic expression of transcription factors may have the potential to induce the conversion of any cell type into another. Fibroblast cells can be converted into embryonic stem cell-like cells, neural cells, cardiomyocytes, macrophage-like cells as well as blood progenitors. Additionally, the conversion of astrocytes into neurons or neural stem cells into monocytes has been demonstrated. Nowadays, in the era of systems biology, continuously growing holistic data sets are providing increasing insights into core transcriptional networks and cellular signaling pathways. This knowledge enables cell biologists to understand how cellular fate is determined and how it could be manipulated. As a consequence for biomedical applications, it might be soon possible to convert patient specific somatic cells directly into desired transplantable other cell types. The clinical value, however, of such reprogrammed cells is currently limited due to the invasiveness of methods applied to induce reprogramming factor activity. This review will focus on experimental strategies to ectopically induce cell fate modulators. We will emphasize those strategies that enable efficient and robust overexpression of transcription factors by minimal genetic alterations of the host genome. Furthermore, we will discuss procedures devoid of any genomic manipulation, such as the direct delivery of mRNA, proteins, or the use of small molecules. By this, we aim to give a comprehensive overview on state of the art techniques that harbor the potential to generate safe reprogrammed cells for clinical applications.

  7. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    Science.gov (United States)

    Meng, Jia; Zhang, Jianqiu(Michelle); Qi, Yuan(Alan); Chen, Yidong; Huang, Yufei

    2010-12-01

    The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ([InlineEquation not available: see fulltext.]) status and Estrogen Receptor negative ([InlineEquation not available: see fulltext.]) status, respectively.

  8. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    Directory of Open Access Journals (Sweden)

    Qi Yuan(Alan

    2010-01-01

    Full Text Available Abstract The problem of uncovering transcriptional regulation by transcription factors (TFs based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ( status and Estrogen Receptor negative ( status, respectively.

  9. A stochastic differential equation model for transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Quirk Michelle D

    2007-05-01

    Full Text Available Abstract Background This work explores the quantitative characteristics of the local transcriptional regulatory network based on the availability of time dependent gene expression data sets. The dynamics of the gene expression level are fitted via a stochastic differential equation model, yielding a set of specific regulators and their contribution. Results We show that a beta sigmoid function that keeps track of temporal parameters is a novel prototype of a regulatory function, with the effect of improving the performance of the profile prediction. The stochastic differential equation model follows well the dynamic of the gene expression levels. Conclusion When adapted to biological hypotheses and combined with a promoter analysis, the method proposed here leads to improved models of the transcriptional regulatory networks.

  10. Network based transcription factor analysis of regenerating axolotl limbs

    Directory of Open Access Journals (Sweden)

    Cameron Jo Ann

    2011-03-01

    Full Text Available Abstract Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets. Network analysis showed that TGF-β1 and fibronectin (FN lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem

  11. Auxin and ethylene induce flavonol accumulation through distinct transcriptional networks.

    Science.gov (United States)

    Lewis, Daniel R; Ramirez, Melissa V; Miller, Nathan D; Vallabhaneni, Prashanthi; Ray, W Keith; Helm, Richard F; Winkel, Brenda S J; Muday, Gloria K

    2011-05-01

    Auxin and ethylene are key regulators of plant growth and development, and thus the transcriptional networks that mediate responses to these hormones have been the subject of intense research. This study dissected the hormonal cross talk regulating the synthesis of flavonols and examined their impact on root growth and development. We analyzed the effects of auxin and an ethylene precursor on roots of wild-type and hormone-insensitive Arabidopsis (Arabidopsis thaliana) mutants at the transcript, protein, and metabolite levels at high spatial and temporal resolution. Indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylic acid (ACC) differentially increased flavonol pathway transcripts and flavonol accumulation, altering the relative abundance of quercetin and kaempferol. The IAA, but not ACC, response is lost in the transport inhibitor response1 (tir1) auxin receptor mutant, while ACC responses, but not IAA responses, are lost in ethylene insensitive2 (ein2) and ethylene resistant1 (etr1) ethylene signaling mutants. A kinetic analysis identified increases in transcripts encoding the transcriptional regulators MYB12, Transparent Testa Glabra1, and Production of Anthocyanin Pigment after hormone treatments, which preceded increases in transcripts encoding flavonoid biosynthetic enzymes. In addition, myb12 mutants were insensitive to the effects of auxin and ethylene on flavonol metabolism. The equivalent phenotypes for transparent testa4 (tt4), which makes no flavonols, and tt7, which makes kaempferol but not quercetin, showed that quercetin derivatives are the inhibitors of basipetal root auxin transport, gravitropism, and elongation growth. Collectively, these experiments demonstrate that auxin and ethylene regulate flavonol biosynthesis through distinct signaling networks involving TIR1 and EIN2/ETR1, respectively, both of which converge on MYB12. This study also provides new evidence that quercetin is the flavonol that modulates basipetal auxin transport.

  12. Inferring the role of transcription factors in regulatory networks

    Directory of Open Access Journals (Sweden)

    Le Borgne Michel

    2008-05-01

    Full Text Available Abstract Background Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays. Results We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of E. coli extracted from the literature (1529 nodes and 3802 edges, and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to S. cerevisiae transcriptional network (2419 nodes and 4344 interactions, by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions. In addition, we report predictions for 14.5% of all interactions. Conclusion Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine

  13. Evolution of transcriptional networks in yeast: alternative teams of transcriptional factors for different species

    Directory of Open Access Journals (Sweden)

    Adriana Muñoz

    2016-11-01

    Full Text Available Abstract Background The diversity in eukaryotic life reflects a diversity in regulatory pathways. Nocedal and Johnson argue that the rewiring of gene regulatory networks is a major force for the diversity of life, that changes in regulation can create new species. Results We have created a method (based on our new “ping-pong algorithm for detecting more complicated rewirings, where several transcription factors can substitute for one or more transcription factors in the regulation of a family of co-regulated genes. An example is illustrative. A rewiring has been reported by Hogues et al. that RAP1 in Saccharomyces cerevisiae substitutes for TBF1/CBF1 in Candida albicans for ribosomal RP genes. There one transcription factor substitutes for another on some collection of genes. Such a substitution is referred to as a “rewiring”. We agree with this finding of rewiring as far as it goes but the situation is more complicated. Many transcription factors can regulate a gene and our algorithm finds that in this example a “team” (or collection of three transcription factors including RAP1 substitutes for TBF1 for 19 genes. The switch occurs for a branch of the phylogenetic tree containing 10 species (including Saccharomyces cerevisiae, while the remaining 13 species (Candida albicans are regulated by TBF1. Conclusions To gain insight into more general evolutionary mechanisms, we have created a mathematical algorithm that finds such general switching events and we prove that it converges. Of course any such computational discovery should be validated in the biological tests. For each branch of the phylogenetic tree and each gene module, our algorithm finds a sub-group of co-regulated genes and a team of transcription factors that substitutes for another team of transcription factors. In most cases the signal will be small but in some cases we find a strong signal of switching. We report our findings for 23 Ascomycota fungi species.

  14. Identification of hoxb1b downstream genes: hoxb1b as a regulatory factor controlling transcriptional networks and cell movement during zebrafish gastrulation

    NARCIS (Netherlands)

    van den Akker, W.M.; Durston, A.J.; Spaink, H.P.

    2010-01-01

    Hox proteins are homeobox containing transcription factors that play important roles in patterning the presumptive central nervous system and the axial mesoderm in the early vertebrate embryo. Hox genes are first expressed during gastrula stages and recent studies suggest that their function goes be

  15. Partially observed bipartite network analysis to identify predictive connections in transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Woolf Peter J

    2011-05-01

    Full Text Available Abstract Background Messenger RNA expression is regulated by a complex interplay of different regulatory proteins. Unfortunately, directly measuring the individual activity of these regulatory proteins is difficult, leaving us with only the resulting gene expression pattern as a marker for the underlying regulatory network or regulator-gene associations. Furthermore, traditional methods to predict these regulator-gene associations do not define the relative importance of each association, leading to a large number of connections in the global regulatory network that, although true, are not useful. Results Here we present a Bayesian method that identifies which known transcriptional relationships in a regulatory network are consistent with a given body of static gene expression data by eliminating the non-relevant ones. The Partially Observed Bipartite Network (POBN approach developed here is tested using E. coli expression data and a transcriptional regulatory network derived from RegulonDB. When the regulatory network for E. coli was integrated with 266 E. coli gene chip observations, POBN identified 93 out of 570 connections that were either inconsistent or not adequately supported by the expression data. Conclusion POBN provides a systematic way to integrate known transcriptional networks with observed gene expression data to better identify which transcriptional pathways are likely responsible for the observed gene expression pattern.

  16. Regulation of the BMP Signaling-Responsive Transcriptional Network in the Drosophila Embryo.

    Science.gov (United States)

    Deignan, Lisa; Pinheiro, Marco T; Sutcliffe, Catherine; Saunders, Abbie; Wilcockson, Scott G; Zeef, Leo A H; Donaldson, Ian J; Ashe, Hilary L

    2016-07-01

    The BMP signaling pathway has a conserved role in dorsal-ventral axis patterning during embryonic development. In Drosophila, graded BMP signaling is transduced by the Mad transcription factor and opposed by the Brinker repressor. In this study, using the Drosophila embryo as a model, we combine RNA-seq with Mad and Brinker ChIP-seq to decipher the BMP-responsive transcriptional network underpinning differentiation of the dorsal ectoderm during dorsal-ventral axis patterning. We identify multiple new BMP target genes, including positive and negative regulators of EGF signaling. Manipulation of EGF signaling levels by loss- and gain-of-function studies reveals that EGF signaling negatively regulates embryonic BMP-responsive transcription. Therefore, the BMP gene network has a self-regulating property in that it establishes a balance between its activity and that of the antagonistic EGF signaling pathway to facilitate correct patterning. In terms of BMP-dependent transcription, we identify key roles for the Zelda and Zerknüllt transcription factors in establishing the resulting expression domain, and find widespread binding of insulator proteins to the Mad and Brinker-bound genomic regions. Analysis of embryos lacking the BEAF-32 insulator protein shows reduced transcription of a peak BMP target gene and a reduction in the number of amnioserosa cells, the fate specified by peak BMP signaling. We incorporate our findings into a model for Mad-dependent activation, and discuss its relevance to BMP signal interpretation in vertebrates.

  17. Transcriptional regulation and steady-state modeling of metabolic networks

    DEFF Research Database (Denmark)

    Zelezniak, Aleksej

    understanding underlying the operating principles of metabolic networks. Cellular responses to environmental perturbations and genetic/epigenetic modifications are to a large extent controlled through transcription, which is one of the fundamental mechanism/means of cellular regulation. An important question...... cases, the objective of the regulation appears to be metabolite-oriented as opposed to pathway-oriented. The study thus provides a fundamental and novel view of metabolic network regulation in Saccharomyces cerevisiae. Metabolism is a conserved system across all domains of life. Nowadays, metabolism has......: what are the components of the systems, how are the different components interconnected and how do these networks perform the functions that make the resulting system behavior? Modern analytical technologies allow us to unravel the constituents and interactions happening in a given system; however...

  18. Transcriptional networks-crops, clocks, and abiotic stress.

    Science.gov (United States)

    Gehan, Malia A; Greenham, Kathleen; Mockler, Todd C; McClung, C Robertson

    2015-04-01

    Several factors affect the yield potential and geographical range of crops including the circadian clock, water availability, and seasonal temperature changes. In order to sustain and increase plant productivity on marginal land in the face of both biotic and abiotic stresses, we need to more efficiently generate stress-resistant crops through marker-assisted breeding, genetic modification, and new genome-editing technologies. To leverage these strategies for producing the next generation of crops, future transcriptomic data acquisition should be pursued with an appropriate temporal design and analyzed with a network-centric approach. The following review focuses on recent developments in abiotic stress transcriptional networks in economically important crops and will highlight the utility of correlation-based network analysis and applications.

  19. A PBX1 transcriptional network controls dopaminergic neuron development and is impaired in Parkinson's disease.

    Science.gov (United States)

    Villaescusa, J Carlos; Li, Bingsi; Toledo, Enrique M; Rivetti di Val Cervo, Pia; Yang, Shanzheng; Stott, Simon Rw; Kaiser, Karol; Islam, Saiful; Gyllborg, Daniel; Laguna-Goya, Rocio; Landreh, Michael; Lönnerberg, Peter; Falk, Anna; Bergman, Tomas; Barker, Roger A; Linnarsson, Sten; Selleri, Licia; Arenas, Ernest

    2016-09-15

    Pre-B-cell leukemia homeobox (PBX) transcription factors are known to regulate organogenesis, but their molecular targets and function in midbrain dopaminergic neurons (mDAn) as well as their role in neurodegenerative diseases are unknown. Here, we show that PBX1 controls a novel transcriptional network required for mDAn specification and survival, which is sufficient to generate mDAn from human stem cells. Mechanistically, PBX1 plays a dual role in transcription by directly repressing or activating genes, such as Onecut2 to inhibit lateral fates during embryogenesis, Pitx3 to promote mDAn development, and Nfe2l1 to protect from oxidative stress. Notably, PBX1 and NFE2L1 levels are severely reduced in dopaminergic neurons of the substantia nigra of Parkinson's disease (PD) patients and decreased NFE2L1 levels increases damage by oxidative stress in human midbrain cells. Thus, our results reveal novel roles for PBX1 and its transcriptional network in mDAn development and PD, opening the door for new therapeutic interventions.

  20. Integrated cellular network of transcription regulations and protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Chen Bor-Sen

    2010-03-01

    Full Text Available Abstract Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

  1. Human-specific transcriptional networks in the brain.

    Science.gov (United States)

    Konopka, Genevieve; Friedrich, Tara; Davis-Turak, Jeremy; Winden, Kellen; Oldham, Michael C; Gao, Fuying; Chen, Leslie; Wang, Guang-Zhong; Luo, Rui; Preuss, Todd M; Geschwind, Daniel H

    2012-08-23

    Understanding human-specific patterns of brain gene expression and regulation can provide key insights into human brain evolution and speciation. Here, we use next-generation sequencing, and Illumina and Affymetrix microarray platforms, to compare the transcriptome of human, chimpanzee, and macaque telencephalon. Our analysis reveals a predominance of genes differentially expressed within human frontal lobe and a striking increase in transcriptional complexity specific to the human lineage in the frontal lobe. In contrast, caudate nucleus gene expression is highly conserved. We also identify gene coexpression signatures related to either neuronal processes or neuropsychiatric diseases, including a human-specific module with CLOCK as its hub gene and another module enriched for neuronal morphological processes and genes coexpressed with FOXP2, a gene important for language evolution. These data demonstrate that transcriptional networks have undergone evolutionary remodeling even within a given brain region, providing a window through which to view the foundation of uniquely human cognitive capacities.

  2. SAGA: a hybrid search algorithm for Bayesian Network structure learning of transcriptional regulatory networks.

    Science.gov (United States)

    Adabor, Emmanuel S; Acquaah-Mensah, George K; Oduro, Francis T

    2015-02-01

    Bayesian Networks have been used for the inference of transcriptional regulatory relationships among genes, and are valuable for obtaining biological insights. However, finding optimal Bayesian Network (BN) is NP-hard. Thus, heuristic approaches have sought to effectively solve this problem. In this work, we develop a hybrid search method combining Simulated Annealing with a Greedy Algorithm (SAGA). SAGA explores most of the search space by undergoing a two-phase search: first with a Simulated Annealing search and then with a Greedy search. Three sets of background-corrected and normalized microarray datasets were used to test the algorithm. BN structure learning was also conducted using the datasets, and other established search methods as implemented in BANJO (Bayesian Network Inference with Java Objects). The Bayesian Dirichlet Equivalence (BDe) metric was used to score the networks produced with SAGA. SAGA predicted transcriptional regulatory relationships among genes in networks that evaluated to higher BDe scores with high sensitivities and specificities. Thus, the proposed method competes well with existing search algorithms for Bayesian Network structure learning of transcriptional regulatory networks.

  3. In silico Transcriptional Regulatory Networks Involved in Tomato Fruit Ripening.

    Science.gov (United States)

    Arhondakis, Stilianos; Bita, Craita E; Perrakis, Andreas; Manioudaki, Maria E; Krokida, Afroditi; Kaloudas, Dimitrios; Kalaitzis, Panagiotis

    2016-01-01

    Tomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs) which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37, and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening.

  4. In silico transcriptional regulatory networks involved in tomato fruit ripening

    Directory of Open Access Journals (Sweden)

    Stilianos Arhondakis

    2016-08-01

    Full Text Available ABSTRACTTomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37 and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening.

  5. Identification and characterization of transcription networks in environmentally significant species

    Energy Technology Data Exchange (ETDEWEB)

    Lawrence, Charles E.; McCue, Lee Ann

    2005-11-30

    Understanding the regulation of gene expression, transcription regulation in particular, is one of the grand challenges of molecular biology. Transcription regulation is arguably the most important foundation of cellular function, since it exerts the most fundamental control of the abundance of virtually all of a cell's functional macromolecules. Nevertheless, this process, perhaps because of its difficulty, has been the subject of only a limited number of genomic level analyses. We have undertaken bioinformatics projects to address this issue by developing (1) a cross-species comparison method (i.e. phylogenetic footprinting) for the identification of transcription factor binding sites, (2) a Bayesian clustering method to identify regulons, (3) an improved scanning algorithm that uses a position weight matrix and several related species sequence data to locate transcription factor binding sites, and (4) a method to predict cognate binding sites for transcription factors of unknown specificity. These bioinformatics methods were developed using the model proteobacterium Escherichia coli, with further applications to the genomes of environmentally significant microbes (Rhodopseudomonas palustris, Shewanella oneidensis) in later years of the grant.

  6. Genomic dissection of conserved transcriptional regulation in intestinal epithelial cells

    Science.gov (United States)

    Camp, J. Gray; Weiser, Matthew; Cocchiaro, Jordan L.; Kingsley, David M.; Furey, Terrence S.; Sheikh, Shehzad Z.; Rawls, John F.

    2017-01-01

    The intestinal epithelium serves critical physiologic functions that are shared among all vertebrates. However, it is unknown how the transcriptional regulatory mechanisms underlying these functions have changed over the course of vertebrate evolution. We generated genome-wide mRNA and accessible chromatin data from adult intestinal epithelial cells (IECs) in zebrafish, stickleback, mouse, and human species to determine if conserved IEC functions are achieved through common transcriptional regulation. We found evidence for substantial common regulation and conservation of gene expression regionally along the length of the intestine from fish to mammals and identified a core set of genes comprising a vertebrate IEC signature. We also identified transcriptional start sites and other putative regulatory regions that are differentially accessible in IECs in all 4 species. Although these sites rarely showed sequence conservation from fish to mammals, surprisingly, they drove highly conserved IEC expression in a zebrafish reporter assay. Common putative transcription factor binding sites (TFBS) found at these sites in multiple species indicate that sequence conservation alone is insufficient to identify much of the functionally conserved IEC regulatory information. Among the rare, highly sequence-conserved, IEC-specific regulatory regions, we discovered an ancient enhancer upstream from her6/HES1 that is active in a distinct population of Notch-positive cells in the intestinal epithelium. Together, these results show how combining accessible chromatin and mRNA datasets with TFBS prediction and in vivo reporter assays can reveal tissue-specific regulatory information conserved across 420 million years of vertebrate evolution. We define an IEC transcriptional regulatory network that is shared between fish and mammals and establish an experimental platform for studying how evolutionarily distilled regulatory information commonly controls IEC development and physiology. PMID

  7. Analysis of the transcriptional networks underpinning the activation of murine macrophages by inflammatory mediators

    Science.gov (United States)

    Raza, Sobia; Barnett, Mark W.; Barnett-Itzhaki, Zohar; Amit, Ido; Hume, David A.; Freeman, Tom C.

    2014-01-01

    Macrophages respond to the TLR4 agonist LPS with a sequential transcriptional cascade controlled by a complex regulatory network of signaling pathways and transcription factors. At least two distinct pathways are currently known to be engaged by TLR4 and are distinguished by their dependence on the adaptor molecule MyD88. We have used gene expression microarrays to define the effects of each of three variables—LPS dose, LPS versus IFN-β and -γ, and genetic background—on the transcriptional response of mouse BMDMs. Analysis of correlation networks generated from the data has identified subnetworks or modules within the macrophage transcriptional network that are activated selectively by these variables. We have identified mouse strain-specific signatures, including a module enriched for SLE susceptibility candidates. In the modules of genes unique to different treatments, we found a module of genes induced by type-I IFN but not by LPS treatment, suggesting another layer of complexity in the LPS-TLR4 signaling feedback control. We also observe that the activation of the complement system, in common with the known activation of MHC class 2 genes, is reliant on IFN-γ signaling. Taken together, these data further highlight the exquisite nature of the regulatory systems that control macrophage activation, their likely relevance to disease resistance/susceptibility, and the appropriate response of these cells to proinflammatory stimuli. PMID:24721704

  8. Analysis of the transcriptional networks underpinning the activation of murine macrophages by inflammatory mediators.

    Science.gov (United States)

    Raza, Sobia; Barnett, Mark W; Barnett-Itzhaki, Zohar; Amit, Ido; Hume, David A; Freeman, Tom C

    2014-08-01

    Macrophages respond to the TLR4 agonist LPS with a sequential transcriptional cascade controlled by a complex regulatory network of signaling pathways and transcription factors. At least two distinct pathways are currently known to be engaged by TLR4 and are distinguished by their dependence on the adaptor molecule MyD88. We have used gene expression microarrays to define the effects of each of three variables--LPS dose, LPS versus IFN-β and -γ, and genetic background--on the transcriptional response of mouse BMDMs. Analysis of correlation networks generated from the data has identified subnetworks or modules within the macrophage transcriptional network that are activated selectively by these variables. We have identified mouse strain-specific signatures, including a module enriched for SLE susceptibility candidates. In the modules of genes unique to different treatments, we found a module of genes induced by type-I IFN but not by LPS treatment, suggesting another layer of complexity in the LPS-TLR4 signaling feedback control. We also observe that the activation of the complement system, in common with the known activation of MHC class 2 genes, is reliant on IFN-γ signaling. Taken together, these data further highlight the exquisite nature of the regulatory systems that control macrophage activation, their likely relevance to disease resistance/susceptibility, and the appropriate response of these cells to proinflammatory stimuli.

  9. Inferring regulatory element landscapes and transcription factor networks from cancer methylomes.

    Science.gov (United States)

    Yao, Lijing; Shen, Hui; Laird, Peter W; Farnham, Peggy J; Berman, Benjamin P

    2015-05-21

    Recent studies indicate that DNA methylation can be used to identify transcriptional enhancers, but no systematic approach has been developed for genome-wide identification and analysis of enhancers based on DNA methylation. We describe ELMER (Enhancer Linking by Methylation/Expression Relationships), an R-based tool that uses DNA methylation to identify enhancers and correlates enhancer state with expression of nearby genes to identify transcriptional targets. Transcription factor motif analysis of enhancers is coupled with expression analysis of transcription factors to infer upstream regulators. Using ELMER, we investigated more than 2,000 tumor samples from The Cancer Genome Atlas. We identified networks regulated by known cancer drivers such as GATA3 and FOXA1 (breast cancer), SOX17 and FOXA2 (endometrial cancer), and NFE2L2, SOX2, and TP63 (squamous cell lung cancer). We also identified novel networks with prognostic associations, including RUNX1 in kidney cancer. We propose ELMER as a powerful new paradigm for understanding the cis-regulatory interface between cancer-associated transcription factors and their functional target genes.

  10. Integration and diversity of the regulatory network composed of Maf and CNC families of transcription factors.

    Science.gov (United States)

    Motohashi, Hozumi; O'Connor, Tania; Katsuoka, Fumiki; Engel, James Douglas; Yamamoto, Masayuki

    2002-07-10

    Recent progress in the analysis of transcriptional regulation has revealed the presence of an exquisite functional network comprising the Maf and Cap 'n' collar (CNC) families of regulatory proteins, many of which have been isolated. Among Maf factors, large Maf proteins are important in the regulation of embryonic development and cell differentiation, whereas small Maf proteins serve as obligatory heterodimeric partner molecules for members of the CNC family. Both Maf homodimers and CNC-small Maf heterodimers bind to the Maf recognition element (MARE). Since the MARE contains a consensus TRE sequence recognized by AP-1, Jun and Fos family members may act to compete or interfere with the function of CNC-small Maf heterodimers. Overall then, the quantitative balance of transcription factors interacting with the MARE determines its transcriptional activity. Many putative MARE-dependent target genes such as those induced by antioxidants and oxidative stress are under concerted regulation by the CNC family member Nrf2, as clearly proven by mouse germline mutagenesis. Since these genes represent a vital aspect of the cellular defense mechanism against oxidative stress, Nrf2-null mutant mice are highly sensitive to xenobiotic and oxidative insults. Deciphering the molecular basis of the regulatory network composed of Maf and CNC families of transcription factors will undoubtedly lead to a new paradigm for the cooperative function of transcription factors.

  11. The AP-1 transcription factor Fra1 inhibits follicular B cell differentiation into plasma cells.

    Science.gov (United States)

    Grötsch, Bettina; Brachs, Sebastian; Lang, Christiane; Luther, Julia; Derer, Anja; Schlötzer-Schrehardt, Ursula; Bozec, Aline; Fillatreau, Simon; Berberich, Ingolf; Hobeika, Elias; Reth, Michael; Wagner, Erwin F; Schett, Georg; Mielenz, Dirk; David, Jean-Pierre

    2014-10-20

    The cornerstone of humoral immunity is the differentiation of B cells into antibody-secreting plasma cells. This process is tightly controlled by a regulatory gene network centered on the transcriptional repressor B lymphocyte-induced maturation protein 1 (Blimp1). Proliferation of activated B cells is required to foster Blimp1 expression but needs to be terminated to avoid overshooting immune reactions. Activator protein 1 (AP-1) transcription factors become quickly up-regulated upon B cell activation. We demonstrate that Fra1, a Fos member of AP-1, enhances activation-induced cell death upon induction in activated B cells. Moreover, mice with B cell-specific deletion of Fra1 show enhanced plasma cell differentiation and exacerbated antibody responses. In contrast, transgenic overexpression of Fra1 blocks plasma cell differentiation and immunoglobulin production, which cannot be rescued by Bcl2. On the molecular level, Fra1 represses Blimp1 expression and interferes with binding of the activating AP-1 member c-Fos to the Blimp1 promoter. Conversely, overexpression of c-Fos in Fra1 transgenic B cells releases Blimp1 repression. As Fra1 lacks transcriptional transactivation domains, we propose that Fra1 inhibits Blimp1 expression and negatively controls plasma cell differentiation through binding to the Blimp1 promoter. In summary, we demonstrate that Fra1 negatively controls plasma cell differentiation by repressing Blimp1 expression.

  12. Modular Transcriptional Networks of the Host Pulmonary Response during Early and Late Pneumococcal Pneumonia.

    Science.gov (United States)

    Scicluna, Brendon P; van Lieshout, Miriam H; Blok, Dana C; Florquin, Sandrine; van der Poll, Tom

    2015-05-12

    Streptococcus pneumoniae (Spneu) remains the most lethal bacterial pathogen and the dominant agent of community-acquired pneumonia. Treatment has perennially focused on the use of antibiotics, albeit scrutinized due to the occurrence of antibiotic-resistant Spneu strains. Immunomodulatory strategies have emerged as potential treatment options. Although promising, immunomodulation can lead to improper tissue functions either at steady state or upon infectious challenge. This argues for the availability of tools to enable a detailed assessment of whole pulmonary functions during the course of infection, not only those functions biased to the defense response. Thus, through the use of an unbiased tissue microarray and bioinformatics approach, we aimed to construct a comprehensive map of whole-lung transcriptional activity and cellular pathways during the course of pneumococcal pneumonia. We performed genome-wide transcriptional analysis of whole lungs before and 6 and 48 h after Spneu infection in mice. The 4,000 most variable transcripts across all samples were used to assemble a gene coexpression network comprising 13 intercorrelating modules (clusters of genes). Fifty-four percent of this whole-lung transcriptional network was altered 6 and 48 h after Spneu infection. Canonical signaling pathway analysis uncovered known pathways imparting protection, including IL17A/IL17F signaling and previously undetected mechanisms that included lipid metabolism. Through in silico prediction of cell types, pathways were observed to enrich for distinct cell types such as a novel stromal cell lipid metabolism pathway. These cellular mechanisms were furthermore anchored at functional hub genes of cellular fate, differentiation, growth and transcription. Collectively, we provide a benchmark unsupervised map of whole-lung transcriptional relationships and cellular activity during early and late pneumococcal pneumonia.

  13. Genetic Networks in Mouse Retinal Ganglion Cells

    Directory of Open Access Journals (Sweden)

    Felix L Struebing

    2016-09-01

    Full Text Available Retinal ganglion cells (RGCs are the output neuron of the eye, transmitting visual information from the retina through the optic nerve to the brain. The importance of RGCs for vision is demonstrated in blinding diseases where RGCs are lost, such as in glaucoma or after optic nerve injury. In the present study, we hypothesize that normal RGC function is transcriptionally regulated. To test our hypothesis, we examine large retinal expression microarray datasets from recombinant inbred mouse strains in GeneNetwork and define transcriptional networks of RGCs and their subtypes. Two major and functionally distinct transcriptional networks centering around Thy1 and Tubb3 (Class III beta-tubulin were identified. Each network is independently regulated and modulated by unique genomic loci. Meta-analysis of publically available data confirms that RGC subtypes are differentially susceptible to death, with alpha-RGCs and intrinsically photosensitive RGCs (ipRGCs being less sensitive to cell death than other RGC subtypes in a mouse model of glaucoma.

  14. Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.

    Science.gov (United States)

    Krumsiek, Jan; Marr, Carsten; Schroeder, Timm; Theis, Fabian J

    2011-01-01

    Hematopoiesis is an ideal model system for stem cell biology with advanced experimental access. A systems view on the interactions of core transcription factors is important for understanding differentiation mechanisms and dynamics. In this manuscript, we construct a Boolean network to model myeloid differentiation, specifically from common myeloid progenitors to megakaryocytes, erythrocytes, granulocytes and monocytes. By interpreting the hematopoietic literature and translating experimental evidence into Boolean rules, we implement binary dynamics on the resulting 11-factor regulatory network. Our network contains interesting functional modules and a concatenation of mutual antagonistic pairs. The state space of our model is a hierarchical, acyclic graph, typifying the principles of myeloid differentiation. We observe excellent agreement between the steady states of our model and microarray expression profiles of two different studies. Moreover, perturbations of the network topology correctly reproduce reported knockout phenotypes in silico. We predict previously uncharacterized regulatory interactions and alterations of the differentiation process, and line out reprogramming strategies.

  15. Structure of the transcriptional network controlling white-opaque switching in Candida albicans.

    Science.gov (United States)

    Hernday, Aaron D; Lohse, Matthew B; Fordyce, Polly M; Nobile, Clarissa J; DeRisi, Joseph L; Johnson, Alexander D

    2013-10-01

    The human fungal pathogen Candida albicans can switch between two phenotypic cell types, termed 'white' and 'opaque'. Both cell types are heritable for many generations, and the switch between the two types occurs epigenetically, that is, without a change in the primary DNA sequence of the genome. Previous work identified six key transcriptional regulators important for white-opaque switching: Wor1, Wor2, Wor3, Czf1, Efg1, and Ahr1. In this work, we describe the structure of the transcriptional network that specifies the white and opaque cell types and governs the ability to switch between them. In particular, we use a combination of genome-wide chromatin immunoprecipitation, gene expression profiling, and microfluidics-based DNA binding experiments to determine the direct and indirect regulatory interactions that form the switch network. The six regulators are arranged together in a complex, interlocking network with many seemingly redundant and overlapping connections. We propose that the structure (or topology) of this network is responsible for the epigenetic maintenance of the white and opaque states, the switching between them, and the specialized properties of each state.

  16. Inferring yeast cell cycle regulators and interactions using transcription factor activities

    Directory of Open Access Journals (Sweden)

    Galbraith Simon J

    2005-06-01

    Full Text Available Abstract Background Since transcription factors are often regulated at the post-transcriptional level, their activities, rather than expression levels may provide valuable information for investigating functions and their interactions. The recently developed Network Component Analysis (NCA and its generalized form (gNCA provide a robust framework for deducing the transcription factor activities (TFAs from various types of DNA microarray data and transcription factor-gene connectivity. The goal of this work is to demonstrate the utility of TFAs in inferring transcription factor functions and interactions in Saccharomyces cerevisiae cell cycle regulation. Results Using gNCA, we determined 74 TFAs from both wild type and fkh1 fkh2 deletion mutant microarray data encompassing 1529 ORFs. We hypothesized that transcription factors participating in the cell cycle regulation exhibit cyclic activity profiles. This hypothesis was supported by the TFA profiles of known cell cycle factors and was used as a basis to uncover other potential cell cycle factors. By combining the results from both cluster analysis and periodicity analysis, we recovered nearly 90% of the known cell cycle regulators, and identified 5 putative cell cycle-related transcription factors (Dal81, Hap2, Hir2, Mss11, and Rlm1. In addition, by analyzing expression data from transcription factor knockout strains, we determined 3 verified (Ace2, Ndd1, and Swi5 and 4 putative interaction partners (Cha4, Hap2, Fhl1, and Rts2 of the forkhead transcription factors. Sensitivity of TFAs to connectivity errors was determined to provide confidence level of these predictions. Conclusion By subjecting TFA profiles to analyses based upon physiological signatures we were able to identify cell cycle related transcription factors consistent with current literature, transcription factors with potential cell cycle dependent roles, and interactions between transcription factors.

  17. A transcriptional network controlling glial development in the Drosophila visual system.

    Science.gov (United States)

    Bauke, Ann-Christin; Sasse, Sofia; Matzat, Till; Klämbt, Christian

    2015-06-15

    In the nervous system, glial cells need to be specified from a set of progenitor cells. In the developing Drosophila eye, perineurial glia proliferate and differentiate as wrapping glia in response to a neuronal signal conveyed by the FGF receptor pathway. To unravel the underlying transcriptional network we silenced all genes encoding predicted DNA-binding proteins in glial cells using RNAi. Dref and other factors of the TATA box-binding protein-related factor 2 (TRF2) complex were previously predicted to be involved in cellular metabolism and cell growth. Silencing of these genes impaired early glia proliferation and subsequent differentiation. Dref controls proliferation via activation of the Pdm3 transcription factor, whereas glial differentiation is regulated via Dref and the homeodomain protein Cut. Cut expression is controlled independently of Dref by FGF receptor activity. Loss- and gain-of-function studies show that Cut is required for glial differentiation and is sufficient to instruct the formation of membrane protrusions, a hallmark of wrapping glial morphology. Our work discloses a network of transcriptional regulators controlling the progression of a naïve perineurial glia towards the fully differentiated wrapping glia.

  18. A recently evolved transcriptional network controls biofilm development in Candida albicans.

    Science.gov (United States)

    Nobile, Clarissa J; Fox, Emily P; Nett, Jeniel E; Sorrells, Trevor R; Mitrovich, Quinn M; Hernday, Aaron D; Tuch, Brian B; Andes, David R; Johnson, Alexander D

    2012-01-20

    A biofilm is an organized, resilient group of microbes in which individual cells acquire properties, such as drug resistance, that are distinct from those observed in suspension cultures. Here, we describe and analyze the transcriptional network controlling biofilm formation in the pathogenic yeast Candida albicans, whose biofilms are a major source of medical device-associated infections. We have combined genetic screens, genome-wide approaches, and two in vivo animal models to describe a master circuit controlling biofilm formation, composed of six transcription regulators that form a tightly woven network with ∼1,000 target genes. Evolutionary analysis indicates that the biofilm network has rapidly evolved: genes in the biofilm circuit are significantly weighted toward genes that arose relatively recently with ancient genes being underrepresented. This circuit provides a framework for understanding many aspects of biofilm formation by C. albicans in a mammalian host. It also provides insights into how complex cell behaviors can arise from the evolution of transcription circuits.

  19. Altered Transcriptional Control Networks with Trans-Differentiation of Isogenic Mutant KRas NSCLC Models

    Directory of Open Access Journals (Sweden)

    John A Haley

    2014-12-01

    Full Text Available BackgroundThe capacity of cancer cells to undergo epithelial mesenchymal trans-differentiation has been implicated as a factor driving metastasis, through the acquisition of enhanced migratory/invasive cell programs and the engagement of anti-apoptotic mechanisms promoting drug and radiation resistance. Our aim was to define molecular signaling changes associated with mesenchymal trans-differentiation in two KRas mutant NSCLC models. We focused on central transcription and epigenetic regulators predicted to be important for mesenchymal cell survival.Experimental designWe have modeled trans-differentiation and cancer stemness in inducible isogenic mutant KRas H358 and A549 non-small cell lung cell backgrounds. We employed large-scale quantitative phospho-proteomic, proteomic, protein-protein interaction, RNA-Seq and network function prediction approaches to dissect the molecular events associated with the establishment and maintenance of the mesenchymal state.ResultsGene set enrichment and pathway prediction indicated BMI1, KDM5B, RUNX2, MYC/MAX, NFkB, LEF1, and HIF1 target networks were significantly enriched in the trans-differentiation of H358 and A549 NSCLC models. Physical overlaps between multiple networks implicate NR4A1 as an overlapping control between TCF and NFkB pathways. Enrichment correlations also indicated marked decrease in cell cycling, which occurred early in the EMT process. RNA abundance time course studies also indicated early expression of epigenetic and chromatin regulators, including CITED4, RUNX3, CMBX1 and SIRT4. ConclusionsMultiple transcription and epigenetic pathways where altered between epithelial and mesenchymal tumor cell states, notably the polycomb repressive complex-1, HP1g and BAF/Swi-Snf. Network analysis suggests redundancy in the activation and inhibition of pathway regulators, notably factors controlling epithelial cell state.

  20. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    DEFF Research Database (Denmark)

    Soberano de Oliveira, Ana Paula; Patil, Kiran Raosaheb; Nielsen, Jens

    2008-01-01

    with transcriptome data, thereby allowing the identification of key biological features (Reporter Features) around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription...

  1. Studying Dynamic Features in Myocardial Infarction Progression by Integrating miRNA-Transcription Factor Co-Regulatory Networks and Time-Series RNA Expression Data from Peripheral Blood Mononuclear Cells.

    Directory of Open Access Journals (Sweden)

    Hongbo Shi

    Full Text Available Myocardial infarction (MI is a serious heart disease and a leading cause of mortality and morbidity worldwide. Although some molecules (genes, miRNAs and transcription factors (TFs associated with MI have been studied in a specific pathological context, their dynamic characteristics in gene expressions, biological functions and regulatory interactions in MI progression have not been fully elucidated to date. In the current study, we analyzed time-series RNA expression data from peripheral blood mononuclear cells. We observed that significantly differentially expressed genes were sharply up- or down-regulated in the acute phase of MI, and then changed slowly until the chronic phase. Biological functions involved at each stage of MI were identified. Additionally, dynamic miRNA-TF co-regulatory networks were constructed based on the significantly differentially expressed genes and miRNA-TF co-regulatory motifs, and the dynamic interplay of miRNAs, TFs and target genes were investigated. Finally, a new panel of candidate diagnostic biomarkers (STAT3 and ICAM1 was identified to have discriminatory capability for patients with or without MI, especially the patients with or without recurrent events. The results of the present study not only shed new light on the understanding underlying regulatory mechanisms involved in MI progression, but also contribute to the discovery of true diagnostic biomarkers for MI.

  2. Integrative biology identifies shared transcriptional networks in CKD.

    Science.gov (United States)

    Martini, Sebastian; Nair, Viji; Keller, Benjamin J; Eichinger, Felix; Hawkins, Jennifer J; Randolph, Ann; Böger, Carsten A; Gadegbeku, Crystal A; Fox, Caroline S; Cohen, Clemens D; Kretzler, Matthias

    2014-11-01

    A previous meta-analysis of genome-wide association data by the Cohorts for Heart and Aging Research in Genomic Epidemiology and CKDGen consortia identified 16 loci associated with eGFR. To define how each of these single-nucleotide polymorphisms (SNPs) could affect renal function, we integrated GFR-associated loci with regulatory pathways, producing a molecular map of CKD. In kidney biopsy specimens from 157 European subjects representing nine different CKDs, renal transcript levels for 18 genes in proximity to the SNPs significantly correlated with GFR. These 18 genes were mapped into their biologic context by testing coregulated transcripts for enriched pathways. A network of 97 pathways linked by shared genes was constructed and characterized. Of these pathways, 56 pathways were reported previously to be associated with CKD; 41 pathways without prior association with CKD were ranked on the basis of the number of candidate genes connected to the respective pathways. All pathways aggregated into a network of two main clusters comprising inflammation- and metabolism-related pathways, with the NRF2-mediated oxidative stress response pathway serving as the hub between the two clusters. In all, 78 pathways and 95% of the connections among those pathways were verified in an independent North American biopsy cohort. Disease-specific analyses showed that most pathways are shared between sets of three diseases, with closest interconnection between lupus nephritis, IgA nephritis, and diabetic nephropathy. Taken together, the network integrates candidate genes from genome-wide association studies into their functional context, revealing interactions and defining established and novel biologic mechanisms of renal impairment in renal diseases.

  3. Rearrangements of the transcriptional regulatory networks of metabolic pathways in fungi

    OpenAIRE

    Lavoie, Hugo; Hogues, Hervé; Whiteway, Malcolm

    2009-01-01

    Growing evidence suggests that transcriptional regulatory networks in many organisms are highly flexible. Here, we discuss the evolution of transcriptional regulatory networks governing the metabolic machinery of sequenced ascomycetes. In particular, recent work has shown that transcriptional rewiring is common in regulons controlling processes such as production of ribosome components and metabolism of carbohydrates and lipids. We note that dramatic rearrangements of the transcriptional regu...

  4. Regulation of Transcriptional Networks by PKC Isozymes: Identification of c-Rel as a Key Transcription Factor for PKC-Regulated Genes.

    Directory of Open Access Journals (Sweden)

    Rachana Garg

    Full Text Available Activation of protein kinase C (PKC, a family of serine-threonine kinases widely implicated in cancer progression, has major impact on gene expression. In a recent genome-wide analysis of prostate cancer cells we identified distinctive gene expression profiles controlled by individual PKC isozymes and highlighted a prominent role for PKCδ in transcriptional activation.Here we carried out a thorough bioinformatics analysis to dissect transcriptional networks controlled by PKCα, PKCδ, and PKCε, the main diacylglycerol/phorbol ester PKCs expressed in prostate cancer cells. Despite the remarkable differences in the patterns of transcriptional responsive elements (REs regulated by each PKC, we found that c-Rel represents the most frequent RE in promoters regulated by all three PKCs. In addition, promoters of PKCδ-regulated genes were particularly enriched with REs for CREB, NF-E2, RREB, SRF, Oct-1, Evi-1, and NF-κB. Most notably, by using transcription factor-specific RNAi we were able to identify subsets of PKCδ-regulated genes modulated by c-Rel and CREB. Furthermore, PKCδ-regulated genes condensed under the c-Rel transcriptional regulation display significant functional interconnections with biological processes such as angiogenesis, inflammatory response, and cell motility.Our study identified candidate transcription factors in the promoters of PKC regulated genes, in particular c-Rel was found as a key transcription factor in the control of PKCδ-regulated genes. The deconvolution of PKC-regulated transcriptional networks and their nodes may greatly help in the identification of PKC effectors and have significant therapeutics implications.

  5. Technical Advance: Transcription factor, promoter, and enhancer utilization in human myeloid cells

    Science.gov (United States)

    Joshi, Anagha; Pooley, Christopher; Freeman, Tom C.; Lennartsson, Andreas; Babina, Magda; Schmidl, Christian; Geijtenbeek, Teunis; Michoel, Tom; Severin, Jessica; Itoh, Masayoshi; Lassmann, Timo; Kawaji, Hideya; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R. R.; Rehli, Michael; Hume, David A.

    2015-01-01

    The generation of myeloid cells from their progenitors is regulated at the level of transcription by combinatorial control of key transcription factors influencing cell-fate choice. To unravel the global dynamics of this process at the transcript level, we generated transcription profiles for 91 human cell types of myeloid origin by use of CAGE profiling. The CAGE sequencing of these samples has allowed us to investigate diverse aspects of transcription control during myelopoiesis, such as identification of novel transcription factors, miRNAs, and noncoding RNAs specific to the myeloid lineage. We further reconstructed a transcription regulatory network by clustering coexpressed transcripts and associating them with enriched cis-regulatory motifs. With the use of the bidirectional expression as a proxy for enhancers, we predicted over 2000 novel enhancers, including an enhancer 38 kb downstream of IRF8 and an intronic enhancer in the KIT gene locus. Finally, we highlighted relevance of these data to dissect transcription dynamics during progressive maturation of granulocyte precursors. A multifaceted analysis of the myeloid transcriptome is made available (www.myeloidome.roslin.ed.ac.uk). This high-quality dataset provides a powerful resource to study transcriptional regulation during myelopoiesis and to infer the likely functions of unannotated genes in human innate immunity. PMID:25717144

  6. Technical Advance: Transcription factor, promoter, and enhancer utilization in human myeloid cells.

    Science.gov (United States)

    Joshi, Anagha; Pooley, Christopher; Freeman, Tom C; Lennartsson, Andreas; Babina, Magda; Schmidl, Christian; Geijtenbeek, Teunis; Michoel, Tom; Severin, Jessica; Itoh, Masayoshi; Lassmann, Timo; Kawaji, Hideya; Hayashizaki, Yoshihide; Carninci, Piero; Forrest, Alistair R R; Rehli, Michael; Hume, David A

    2015-05-01

    The generation of myeloid cells from their progenitors is regulated at the level of transcription by combinatorial control of key transcription factors influencing cell-fate choice. To unravel the global dynamics of this process at the transcript level, we generated transcription profiles for 91 human cell types of myeloid origin by use of CAGE profiling. The CAGE sequencing of these samples has allowed us to investigate diverse aspects of transcription control during myelopoiesis, such as identification of novel transcription factors, miRNAs, and noncoding RNAs specific to the myeloid lineage. We further reconstructed a transcription regulatory network by clustering coexpressed transcripts and associating them with enriched cis-regulatory motifs. With the use of the bidirectional expression as a proxy for enhancers, we predicted over 2000 novel enhancers, including an enhancer 38 kb downstream of IRF8 and an intronic enhancer in the KIT gene locus. Finally, we highlighted relevance of these data to dissect transcription dynamics during progressive maturation of granulocyte precursors. A multifaceted analysis of the myeloid transcriptome is made available (www.myeloidome.roslin.ed.ac.uk). This high-quality dataset provides a powerful resource to study transcriptional regulation during myelopoiesis and to infer the likely functions of unannotated genes in human innate immunity.

  7. The cis-regulatory logic of the mammalian photoreceptor transcriptional network.

    Directory of Open Access Journals (Sweden)

    Timothy H-C Hsiau

    Full Text Available The photoreceptor cells of the retina are subject to a greater number of genetic diseases than any other cell type in the human body. The majority of more than 120 cloned human blindness genes are highly expressed in photoreceptors. In order to establish an integrative framework in which to understand these diseases, we have undertaken an experimental and computational analysis of the network controlled by the mammalian photoreceptor transcription factors, Crx, Nrl, and Nr2e3. Using microarray and in situ hybridization datasets we have produced a model of this network which contains over 600 genes, including numerous retinal disease loci as well as previously uncharacterized photoreceptor transcription factors. To elucidate the connectivity of this network, we devised a computational algorithm to identify the photoreceptor-specific cis-regulatory elements (CREs mediating the interactions between these transcription factors and their target genes. In vivo validation of our computational predictions resulted in the discovery of 19 novel photoreceptor-specific CREs near retinal disease genes. Examination of these CREs permitted the definition of a simple cis-regulatory grammar rule associated with high-level expression. To test the generality of this rule, we used an expanded form of it as a selection filter to evolve photoreceptor CREs from random DNA sequences in silico. When fused to fluorescent reporters, these evolved CREs drove strong, photoreceptor-specific expression in vivo. This study represents the first systematic identification and in vivo validation of CREs in a mammalian neuronal cell type and lays the groundwork for a systems biology of photoreceptor transcriptional regulation.

  8. Transcriptional networks in the early development of sensory-motor circuits.

    Science.gov (United States)

    Dasen, Jeremy S

    2009-01-01

    The emergence of coordinated locomotor behaviors in vertebrates relies on the establishment of selective connections between discrete populations of neurons present in the spinal cord and peripheral nervous system. The assembly of the circuits necessary for movement presumably requires the generation of many unique cell types to accommodate the intricate connections between motor neurons, sensory neurons, interneurons, and muscle. The specification of diverse neuronal subtypes is mediated largely through networks of transcription factors that operate within progenitor and postmitotic cells. Selective patterns of transcription factor expression appear to define the cell-type-specific cellular programs that govern the axonal guidance decisions and synaptic specificities of neurons, and may lay the foundation through which innate motor behaviors are genetically predetermined. Recent studies on the developmental programs that specify two highly diverse neuronal classes-spinal motor neurons and proprioceptive sensory neurons-have provided important insights into the molecular strategies used in the earliest phases of locomotor circuit assembly. This chapter reviews progress toward elucidating the early transcriptional networks that define neuronal identity in the locomotor system, focusing on the pathways controlling the specific connections of motor neurons and sensory neurons in the formation of simple reflex circuits.

  9. Buffered Qualitative Stability explains the robustness and evolvability of transcriptional networks.

    Science.gov (United States)

    Albergante, Luca; Blow, J Julian; Newman, Timothy J

    2014-09-02

    The gene regulatory network (GRN) is the central decision-making module of the cell. We have developed a theory called Buffered Qualitative Stability (BQS) based on the hypothesis that GRNs are organised so that they remain robust in the face of unpredictable environmental and evolutionary changes. BQS makes strong and diverse predictions about the network features that allow stable responses under arbitrary perturbations, including the random addition of new connections. We show that the GRNs of E. coli, M. tuberculosis, P. aeruginosa, yeast, mouse, and human all verify the predictions of BQS. BQS explains many of the small- and large-scale properties of GRNs, provides conditions for evolvable robustness, and highlights general features of transcriptional response. BQS is severely compromised in a human cancer cell line, suggesting that loss of BQS might underlie the phenotypic plasticity of cancer cells, and highlighting a possible sequence of GRN alterations concomitant with cancer initiation.

  10. Genome Binding and Gene Regulation by Stem Cell Transcription Factors

    NARCIS (Netherlands)

    J.H. Brandsma (Johan)

    2016-01-01

    markdownabstractNearly all cells of an individual organism contain the same genome. However, each cell type transcribes a different set of genes due to the presence of different sets of cell type-specific transcription factors. Such transcription factors bind to regulatory regions such as promoters

  11. An extended gene protein/products Boolean network model including post-transcriptional regulation.

    Science.gov (United States)

    Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Vasciaveo, Alessandro

    2014-05-07

    Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. In this paper we show how it is possible to include the post-transcriptional regulation mechanism (a key process mediated by small non-coding RNA molecules like the miRNAs) into the BN model of a GRN. The enhanced BN model is implemented in a software toolkit (EBNT) that allows to analyze boolean GRNs from both a structural and a dynamic point of view. The open-source toolkit is compatible with available visualization tools like Cytoscape and allows to run detailed analysis of the network topology as well as of its attractors, trajectories, and state-space. In the paper, a small GRN built around the mTOR gene is used to demonstrate the main capabilities of the toolkit. The extended model proposed in this paper opens new opportunities in the study of gene regulation. Several of the successful researches done with the support of BN to understand high-level characteristics of regulatory networks, can now be improved to better understand the role of post-transcriptional regulation for example as a network-wide noise-reduction or stabilization mechanisms.

  12. An extended gene protein/products boolean network model including post-transcriptional regulation

    Science.gov (United States)

    2014-01-01

    Background Networks Biology allows the study of complex interactions between biological systems using formal, well structured, and computationally friendly models. Several different network models can be created, depending on the type of interactions that need to be investigated. Gene Regulatory Networks (GRN) are an effective model commonly used to study the complex regulatory mechanisms of a cell. Unfortunately, given their intrinsic complexity and non discrete nature, the computational study of realistic-sized complex GRNs requires some abstractions. Boolean Networks (BNs), for example, are a reliable model that can be used to represent networks where the possible state of a node is a boolean value (0 or 1). Despite this strong simplification, BNs have been used to study both structural and dynamic properties of real as well as randomly generated GRNs. Results In this paper we show how it is possible to include the post-transcriptional regulation mechanism (a key process mediated by small non-coding RNA molecules like the miRNAs) into the BN model of a GRN. The enhanced BN model is implemented in a software toolkit (EBNT) that allows to analyze boolean GRNs from both a structural and a dynamic point of view. The open-source toolkit is compatible with available visualization tools like Cytoscape and allows to run detailed analysis of the network topology as well as of its attractors, trajectories, and state-space. In the paper, a small GRN built around the mTOR gene is used to demonstrate the main capabilities of the toolkit. Conclusions The extended model proposed in this paper opens new opportunities in the study of gene regulation. Several of the successful researches done with the support of BN to understand high-level characteristics of regulatory networks, can now be improved to better understand the role of post-transcriptional regulation for example as a network-wide noise-reduction or stabilization mechanisms. PMID:25080304

  13. Transcriptional profiling uncovers a network of cholesterol-responsive atherosclerosis target genes.

    Directory of Open Access Journals (Sweden)

    Josefin Skogsberg

    2008-03-01

    Full Text Available Despite the well-documented effects of plasma lipid lowering regimes halting atherosclerosis lesion development and reducing morbidity and mortality of coronary artery disease and stroke, the transcriptional response in the atherosclerotic lesion mediating these beneficial effects has not yet been carefully investigated. We performed transcriptional profiling at 10-week intervals in atherosclerosis-prone mice with human-like hypercholesterolemia and a genetic switch to lower plasma lipoproteins (Ldlr(-/-Apo(100/100Mttp(flox/flox Mx1-Cre. Atherosclerotic lesions progressed slowly at first, then expanded rapidly, and plateaued after advanced lesions formed. Analysis of lesion expression profiles indicated that accumulation of lipid-poor macrophages reached a point that led to the rapid expansion phase with accelerated foam-cell formation and inflammation, an interpretation supported by lesion histology. Genetic lowering of plasma cholesterol (e.g., lipoproteins at this point all together prevented the formation of advanced plaques and parallel transcriptional profiling of the atherosclerotic arterial wall identified 37 cholesterol-responsive genes mediating this effect. Validation by siRNA-inhibition in macrophages incubated with acetylated-LDL revealed a network of eight cholesterol-responsive atherosclerosis genes regulating cholesterol-ester accumulation. Taken together, we have identified a network of atherosclerosis genes that in response to plasma cholesterol-lowering prevents the formation of advanced plaques. This network should be of interest for the development of novel atherosclerosis therapies.

  14. Transcriptional profiling uncovers a network of cholesterol-responsive atherosclerosis target genes.

    Directory of Open Access Journals (Sweden)

    Josefin Skogsberg

    2008-03-01

    Full Text Available Despite the well-documented effects of plasma lipid lowering regimes halting atherosclerosis lesion development and reducing morbidity and mortality of coronary artery disease and stroke, the transcriptional response in the atherosclerotic lesion mediating these beneficial effects has not yet been carefully investigated. We performed transcriptional profiling at 10-week intervals in atherosclerosis-prone mice with human-like hypercholesterolemia and a genetic switch to lower plasma lipoproteins (Ldlr(-/-Apo(100/100Mttp(flox/flox Mx1-Cre. Atherosclerotic lesions progressed slowly at first, then expanded rapidly, and plateaued after advanced lesions formed. Analysis of lesion expression profiles indicated that accumulation of lipid-poor macrophages reached a point that led to the rapid expansion phase with accelerated foam-cell formation and inflammation, an interpretation supported by lesion histology. Genetic lowering of plasma cholesterol (e.g., lipoproteins at this point all together prevented the formation of advanced plaques and parallel transcriptional profiling of the atherosclerotic arterial wall identified 37 cholesterol-responsive genes mediating this effect. Validation by siRNA-inhibition in macrophages incubated with acetylated-LDL revealed a network of eight cholesterol-responsive atherosclerosis genes regulating cholesterol-ester accumulation. Taken together, we have identified a network of atherosclerosis genes that in response to plasma cholesterol-lowering prevents the formation of advanced plaques. This network should be of interest for the development of novel atherosclerosis therapies.

  15. CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

    Directory of Open Access Journals (Sweden)

    Czaja Lisa F

    2006-02-01

    Full Text Available Abstract Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

  16. Reverse engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL.

    Science.gov (United States)

    Della Gatta, Giusy; Palomero, Teresa; Perez-Garcia, Arianne; Ambesi-Impiombato, Alberto; Bansal, Mukesh; Carpenter, Zachary W; De Keersmaecker, Kim; Sole, Xavier; Xu, Luyao; Paietta, Elisabeth; Racevskis, Janis; Wiernik, Peter H; Rowe, Jacob M; Meijerink, Jules P; Califano, Andrea; Ferrando, Adolfo A

    2012-02-26

    The TLX1 and TLX3 transcription factor oncogenes have a key role in the pathogenesis of T cell acute lymphoblastic leukemia (T-ALL). Here we used reverse engineering of global transcriptional networks to decipher the oncogenic regulatory circuit controlled by TLX1 and TLX3. This systems biology analysis defined T cell leukemia homeobox 1 (TLX1) and TLX3 as master regulators of an oncogenic transcriptional circuit governing T-ALL. Notably, a network structure analysis of this hierarchical network identified RUNX1 as a key mediator of the T-ALL induced by TLX1 and TLX3 and predicted a tumor-suppressor role for RUNX1 in T cell transformation. Consistent with these results, we identified recurrent somatic loss-of-function mutations in RUNX1 in human T-ALL. Overall, these results place TLX1 and TLX3 at the top of an oncogenic transcriptional network controlling leukemia development, show the power of network analyses to identify key elements in the regulatory circuits governing human cancer and identify RUNX1 as a tumor-suppressor gene in T-ALL.

  17. Transcriptional networks driving enhancer function in the CFTR gene.

    Science.gov (United States)

    Kerschner, Jenny L; Harris, Ann

    2012-09-01

    A critical cis-regulatory element for the CFTR (cystic fibrosis transmembrane conductance regulator) gene is located in intron 11, 100 kb distal to the promoter, with which it interacts. This sequence contains an intestine-selective enhancer and associates with enhancer signature proteins, such as p300, in addition to tissue-specific TFs (transcription factors). In the present study we identify critical TFs that are recruited to this element and demonstrate their importance in regulating CFTR expression. In vitro DNase I footprinting and EMSAs (electrophoretic mobility-shift assays) identified four cell-type-selective regions that bound TFs in vitro. ChIP (chromatin immunoprecipitation) identified FOXA1/A2 (forkhead box A1/A2), HNF1 (hepatocyte nuclear factor 1) and CDX2 (caudal-type homeobox 2) as in vivo trans-interacting factors. Mutation of their binding sites in the intron 11 core compromised its enhancer activity when measured by reporter gene assay. Moreover, siRNA (small interfering RNA)-mediated knockdown of CDX2 caused a significant reduction in endogenous CFTR transcription in intestinal cells, suggesting that this factor is critical for the maintenance of high levels of CFTR expression in these cells. The ChIP data also demonstrate that these TFs interact with multiple cis-regulatory elements across the CFTR locus, implicating a more global role in intestinal expression of the gene.

  18. Cross-species transcriptional network analysis reveals conservation and variation in response to metal stress in cyanobacteria

    Science.gov (United States)

    2013-01-01

    Background As one of the most dominant bacterial groups on Earth, cyanobacteria play a pivotal role in the global carbon cycling and the Earth atmosphere composition. Understanding their molecular responses to environmental perturbations has important scientific and environmental values. Since important biological processes or networks are often evolutionarily conserved, the cross-species transcriptional network analysis offers a useful strategy to decipher conserved and species-specific transcriptional mechanisms that cells utilize to deal with various biotic and abiotic disturbances, and it will eventually lead to a better understanding of associated adaptation and regulatory networks. Results In this study, the Weighted Gene Co-expression Network Analysis (WGCNA) approach was used to establish transcriptional networks for four important cyanobacteria species under metal stress, including iron depletion and high copper conditions. Cross-species network comparison led to discovery of several core response modules and genes possibly essential to metal stress, as well as species-specific hub genes for metal stresses in different cyanobacteria species, shedding light on survival strategies of cyanobacteria responding to different environmental perturbations. Conclusions The WGCNA analysis demonstrated that the application of cross-species transcriptional network analysis will lead to novel insights to molecular response to environmental changes which will otherwise not be achieved by analyzing data from a single species. PMID:23421563

  19. Targeting the bHLH transcriptional networks by mutated E proteins in experimental glioma.

    Science.gov (United States)

    Beyeler, Sarah; Joly, Sandrine; Fries, Michel; Obermair, Franz-Josef; Burn, Felice; Mehmood, Rashid; Tabatabai, Ghazaleh; Raineteau, Olivier

    2014-10-01

    Glioblastomas (GB) are aggressive primary brain tumors. Helix-loop-helix (HLH, ID proteins) and basic HLH (bHLH, e.g., Olig2) proteins are transcription factors that regulate stem cell proliferation and differentiation throughout development and into adulthood. Their convergence on many oncogenic signaling pathways combined with the observation that their overexpression in GB correlates with poor clinical outcome identifies these transcription factors as promising therapeutic targets. Important dimerization partners of HLH/bHLH proteins are E proteins that are necessary for nuclear translocation and DNA binding. Here, we overexpressed a wild type or a dominant negative form of E47 (dnE47) that lacks its nuclear localization signal thus preventing nuclear translocation of bHLH proteins in long-term glioma cell lines and in glioma-initiating cell lines and analyzed the effects in vitro and in vivo. While overexpression of E47 was sufficient to induce apoptosis in absence of bHLH proteins, dnE47 was necessary to prevent nuclear translocation of Olig2 and to achieve similar proapoptotic responses. Transcriptional analyses revealed downregulation of the antiapoptotic gene BCL2L1 and the proproliferative gene CDC25A as underlying mechanisms. Overexpression of dnE47 in glioma-initiating cell lines with high HLH and bHLH protein levels reduced sphere formation capacities and expression levels of Nestin, BCL2L1, and CDC25A. Finally, the in vivo induction of dnE47 expression in established xenografts prolonged survival. In conclusion, our data introduce a novel approach to jointly neutralize HLH and bHLH transcriptional networks activities, and identify these transcription factors as potential targets in glioma.

  20. Integration of the transcriptional networks regulating limb morphogenesis.

    Science.gov (United States)

    Rabinowitz, Adam H; Vokes, Steven A

    2012-08-15

    The developing limb is one of the best described vertebrate systems for understanding how coordinated gene expression during embryogenesis leads to the structures present in the mature organism. This knowledge, derived from decades of research, is largely based upon gain- and loss-of-function experiments. These studies have provided limited information about how the key signaling pathways interact with each other and the downstream effectors of these pathways. We summarize our current understanding of known genetic interactions in the context of three temporally defined gene regulatory networks. These networks crystallize our current knowledge, depicting a dynamic process involving multiple feedback loops between the ectoderm and mesoderm. At the same time, they highlight the fact that many essential processes are still largely undescribed. Much of the dynamic transcriptional activity occurring during development is regulated by distal cis-regulatory elements. Modern genomic tools have provided new approaches for studying the function of cis-regulatory elements and we discuss the results of these studies in regard to understanding limb development. Ultimately, these genomic techniques will allow scientists to understand how multiple signaling pathways are integrated in space and time to drive gene expression and regulate the formation of the limb.

  1. Unexpected complexity of the Reef-Building Coral Acropora millepora transcription factor network

    Directory of Open Access Journals (Sweden)

    Ravasi Timothy

    2011-04-01

    Full Text Available Abstract Background Coral reefs are disturbed on a global scale by environmental changes including rising sea surface temperatures and ocean acidification. Little is known about how corals respond or adapt to these environmental changes especially at the molecular level. This is mostly because of the paucity of genome-wide studies on corals and the application of systems approaches that incorporate the latter. Like in any other organism, the response of corals to stress is tightly controlled by the coordinated interplay of many transcription factors. Results Here, we develop and apply a new system-wide approach in order to infer combinatorial transcription factor networks of the reef-building coral Acropora millepora. By integrating sequencing-derived transcriptome measurements, a network of physically interacting transcription factors, and phylogenetic network footprinting we were able to infer such a network. Analysis of the network across a phylogenetically broad sample of five species, including human, reveals that despite the apparent simplicity of corals, their transcription factors repertoire and interaction networks seem to be largely conserved. In addition, we were able to identify interactions among transcription factors that appear to be species-specific lending strength to the novel concept of "Taxonomically Restricted Interactions". Conclusions This study provides the first look at transcription factor networks in corals. We identified a transcription factor repertoire encoded by the coral genome and found consistencies of the domain architectures of transcription factors and conserved regulatory subnetworks across eumetazoan species, providing insight into how regulatory networks have evolved.

  2. Coupled transcription and translation within nuclei of mammalian cells.

    Science.gov (United States)

    Iborra, F J; Jackson, D A; Cook, P R

    2001-08-10

    It is widely assumed that the vital processes of transcription and translation are spatially separated in eukaryotes and that no translation occurs in nuclei. We localized translation sites by incubating permeabilized mammalian cells with [3H]lysine or lysyl-transfer RNA tagged with biotin or BODIPY; although most nascent polypeptides were cytoplasmic, some were found in discrete nuclear sites known as transcription "factories." Some of this nuclear translation also depends on concurrent transcription by RNA polymerase II. This coupling is simply explained if nuclear ribosomes translate nascent transcripts as those transcripts emerge from still-engaged RNA polymerases, much as they do in bacteria.

  3. Modeling the effect of transcriptional noise on switching in gene networks in a genetic bistable switch.

    Science.gov (United States)

    Chaudhury, Srabanti

    2015-06-01

    Gene regulatory networks in cells allow transitions between gene expression states under the influence of both intrinsic and extrinsic noise. Here we introduce a new theoretical method to study the dynamics of switching in a two-state gene expression model with positive feedback by explicitly accounting for the transcriptional noise. Within this theoretical framework, we employ a semi-classical path integral technique to calculate the mean switching time starting from either an active or inactive promoter state. Our analytical predictions are in good agreement with Monte Carlo simulations and experimental observations.

  4. Stochastic models of transcription: from single molecules to single cells.

    Science.gov (United States)

    Sanchez, Alvaro; Choubey, Sandeep; Kondev, Jane

    2013-07-15

    Genes in prokaryotic and eukaryotic cells are typically regulated by complex promoters containing multiple binding sites for a variety of transcription factors leading to a specific functional dependence between regulatory inputs and transcriptional outputs. With increasing regularity, the transcriptional outputs from different promoters are being measured in quantitative detail in single-cell experiments thus providing the impetus for the development of quantitative models of transcription. We describe recent progress in developing models of transcriptional regulation that incorporate, to different degrees, the complexity of multi-state promoter dynamics, and its effect on the transcriptional outputs of single cells. The goal of these models is to predict the statistical properties of transcriptional outputs and characterize their variability in time and across a population of cells, as a function of the input concentrations of transcription factors. The interplay between mathematical models of different regulatory mechanisms and quantitative biophysical experiments holds the promise of elucidating the molecular-scale mechanisms of transcriptional regulation in cells, from bacteria to higher eukaryotes. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Using Mutual Information and Answer Set Programming to refine PWM based transcription regulation network

    OpenAIRE

    Aravena, Andres; Guziolowski, Carito; Siegel, Anne; Maass, Alejandro

    2012-01-01

    National audience; Transcriptional regulatory network models can be reconstructed ab initio from DNA sequence data by locating the binding sites, defined by position specific score matrices, and identifying transcription factors by homology with known ones in other organisms. In general the resulting network contains spurious elements, because the pattern matching methods for binding site location have low specificity, while homology to known transcription factors does not always identify cor...

  6. Dynamics of regulatory networks in gastrin-treated adenocarcinoma cells.

    Directory of Open Access Journals (Sweden)

    Naresh Doni Jayavelu

    Full Text Available Understanding gene transcription regulatory networks is critical to deciphering the molecular mechanisms of different cellular states. Most studies focus on static transcriptional networks. In the current study, we used the gastrin-regulated system as a model to understand the dynamics of transcriptional networks composed of transcription factors (TFs and target genes (TGs. The hormone gastrin activates and stimulates signaling pathways leading to various cellular states through transcriptional programs. Dysregulation of gastrin can result in cancerous tumors, for example. However, the regulatory networks involving gastrin are highly complex, and the roles of most of the components of these networks are unknown. We used time series microarray data of AR42J adenocarcinoma cells treated with gastrin combined with static TF-TG relationships integrated from different sources, and we reconstructed the dynamic activities of TFs using network component analysis (NCA. Based on the peak expression of TGs and activity of TFs, we created active sub-networks at four time ranges after gastrin treatment, namely immediate-early (IE, mid-early (ME, mid-late (ML and very late (VL. Network analysis revealed that the active sub-networks were topologically different at the early and late time ranges. Gene ontology analysis unveiled that each active sub-network was highly enriched in a particular biological process. Interestingly, network motif patterns were also distinct between the sub-networks. This analysis can be applied to other time series microarray datasets, focusing on smaller sub-networks that are activated in a cascade, allowing better overview of the mechanisms involved at each time range.

  7. Termination factor Rho: From the control of pervasive transcription to cell fate determination in Bacillus subtilis.

    Science.gov (United States)

    Bidnenko, Vladimir; Nicolas, Pierre; Grylak-Mielnicka, Aleksandra; Delumeau, Olivier; Auger, Sandrine; Aucouturier, Anne; Guerin, Cyprien; Repoila, Francis; Bardowski, Jacek; Aymerich, Stéphane; Bidnenko, Elena

    2017-07-01

    In eukaryotes, RNA species originating from pervasive transcription are regulators of various cellular processes, from the expression of individual genes to the control of cellular development and oncogenesis. In prokaryotes, the function of pervasive transcription and its output on cell physiology is still unknown. Most bacteria possess termination factor Rho, which represses pervasive, mostly antisense, transcription. Here, we investigate the biological significance of Rho-controlled transcription in the Gram-positive model bacterium Bacillus subtilis. Rho inactivation strongly affected gene expression in B. subtilis, as assessed by transcriptome and proteome analysis of a rho-null mutant during exponential growth in rich medium. Subsequent physiological analyses demonstrated that a considerable part of Rho-controlled transcription is connected to balanced regulation of three mutually exclusive differentiation programs: cell motility, biofilm formation, and sporulation. In the absence of Rho, several up-regulated sense and antisense transcripts affect key structural and regulatory elements of these differentiation programs, thereby suppressing motility and biofilm formation and stimulating sporulation. We dissected how Rho is involved in the activity of the cell fate decision-making network, centered on the master regulator Spo0A. We also revealed a novel regulatory mechanism of Spo0A activation through Rho-dependent intragenic transcription termination of the protein kinase kinB gene. Altogether, our findings indicate that distinct Rho-controlled transcripts are functional and constitute a previously unknown built-in module for the control of cell differentiation in B. subtilis. In a broader context, our results highlight the recruitment of the termination factor Rho, for which the conserved biological role is probably to repress pervasive transcription, in highly integrated, bacterium-specific, regulatory networks.

  8. Termination factor Rho: From the control of pervasive transcription to cell fate determination in Bacillus subtilis.

    Directory of Open Access Journals (Sweden)

    Vladimir Bidnenko

    2017-07-01

    Full Text Available In eukaryotes, RNA species originating from pervasive transcription are regulators of various cellular processes, from the expression of individual genes to the control of cellular development and oncogenesis. In prokaryotes, the function of pervasive transcription and its output on cell physiology is still unknown. Most bacteria possess termination factor Rho, which represses pervasive, mostly antisense, transcription. Here, we investigate the biological significance of Rho-controlled transcription in the Gram-positive model bacterium Bacillus subtilis. Rho inactivation strongly affected gene expression in B. subtilis, as assessed by transcriptome and proteome analysis of a rho-null mutant during exponential growth in rich medium. Subsequent physiological analyses demonstrated that a considerable part of Rho-controlled transcription is connected to balanced regulation of three mutually exclusive differentiation programs: cell motility, biofilm formation, and sporulation. In the absence of Rho, several up-regulated sense and antisense transcripts affect key structural and regulatory elements of these differentiation programs, thereby suppressing motility and biofilm formation and stimulating sporulation. We dissected how Rho is involved in the activity of the cell fate decision-making network, centered on the master regulator Spo0A. We also revealed a novel regulatory mechanism of Spo0A activation through Rho-dependent intragenic transcription termination of the protein kinase kinB gene. Altogether, our findings indicate that distinct Rho-controlled transcripts are functional and constitute a previously unknown built-in module for the control of cell differentiation in B. subtilis. In a broader context, our results highlight the recruitment of the termination factor Rho, for which the conserved biological role is probably to repress pervasive transcription, in highly integrated, bacterium-specific, regulatory networks.

  9. A quantitative proteomics approach identifies ETV6 and IKZF1 as new regulators of an ERG-driven transcriptional network.

    Science.gov (United States)

    Unnikrishnan, Ashwin; Guan, Yi F; Huang, Yizhou; Beck, Dominik; Thoms, Julie A I; Peirs, Sofie; Knezevic, Kathy; Ma, Shiyong; de Walle, Inge V; de Jong, Ineke; Ali, Zara; Zhong, Ling; Raftery, Mark J; Taghon, Tom; Larsson, Jonas; MacKenzie, Karen L; Van Vlierberghe, Pieter; Wong, Jason W H; Pimanda, John E

    2016-12-15

    Aberrant stem cell-like gene regulatory networks are a feature of leukaemogenesis. The ETS-related gene (ERG), an important regulator of normal haematopoiesis, is also highly expressed in T-ALL and acute myeloid leukaemia (AML). However, the transcriptional regulation of ERG in leukaemic cells remains poorly understood. In order to discover transcriptional regulators of ERG, we employed a quantitative mass spectrometry-based method to identify factors binding the 321 bp ERG +85 stem cell enhancer region in MOLT-4 T-ALL and KG-1 AML cells. Using this approach, we identified a number of known binders of the +85 enhancer in leukaemic cells along with previously unknown binders, including ETV6 and IKZF1. We confirmed that ETV6 and IKZF1 were also bound at the +85 enhancer in both leukaemic cells and in healthy human CD34(+) haematopoietic stem and progenitor cells. Knockdown experiments confirmed that ETV6 and IKZF1 are transcriptional regulators not just of ERG, but also of a number of genes regulated by a densely interconnected network of seven transcription factors. At last, we show that ETV6 and IKZF1 expression levels are positively correlated with expression of a number of heptad genes in AML and high expression of all nine genes confers poorer overall prognosis.

  10. Transcriptional Amplification in Tumor Cells with Elevated c-Myc

    Science.gov (United States)

    Lin, Charles Y.; Lovén, Jakob; Rahl, Peter B.; Paranal, Ronald M.; Burge, Christopher B.; Bradner, James E.; Lee, Tong Ihn; Young, Richard A.

    2012-01-01

    Summary Elevated expression of the c-Myc transcription factor occurs frequently in human cancers and is associated with tumor aggression and poor clinical outcome. The effect of high levels of c-Myc on global gene regulation is poorly understood, but is widely thought to involve newly activated or repressed “Myc target genes”. We report here that in tumor cells expressing high levels of c-Myc, the transcription factor accumulates in the promoter regions of active genes and causes transcriptional amplification, producing increased levels of transcripts within the cell's gene expression program. Thus, rather than binding and regulating a new set of genes, c-Myc amplifies the output of the existing gene expression program. These results provide an explanation for the diverse effects of oncogenic c-Myc on gene expression in different tumor cells and suggest that transcriptional amplification reduces rate-limiting constraints for tumor cell growth and proliferation. PMID:23021215

  11. Computational methods to dissect cis-regulatory transcriptional networks

    Indian Academy of Sciences (India)

    Vibha Rani

    2007-12-01

    The formation of diverse cell types from an invariant set of genes is governed by biochemical and molecular processes that regulate gene activity. A complete understanding of the regulatory mechanisms of gene expression is the major function of genomics. Computational genomics is a rapidly emerging area for deciphering the regulation of metazoan genes as well as interpreting the results of high-throughput screening. The integration of computer science with biology has expedited molecular modelling and processing of large-scale data inputs such as microarrays, analysis of genomes, transcriptomes and proteomes. Many bioinformaticians have developed various algorithms for predicting transcriptional regulatory mechanisms from the sequence, gene expression and interaction data. This review contains compiled information of various computational methods adopted to dissect gene expression pathways.

  12. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells

    Science.gov (United States)

    Arner, Erik; Daub, Carsten O.; Vitting-Seerup, Kristoffer; Andersson, Robin; Lilje, Berit; Drabløs, Finn; Lennartsson, Andreas; Rönnerblad, Michelle; Hrydziuszko, Olga; Vitezic, Morana; Freeman, Tom C.; Alhendi, Ahmad M. N.; Arner, Peter; Axton, Richard; Baillie, J. Kenneth; Beckhouse, Anthony; Bodega, Beatrice; Briggs, James; Brombacher, Frank; Davis, Margaret; Detmar, Michael; Ehrlund, Anna; Endoh, Mitsuhiro; Eslami, Afsaneh; Fagiolini, Michela; Fairbairn, Lynsey; Faulkner, Geoffrey J.; Ferrai, Carmelo; Fisher, Malcolm E.; Forrester, Lesley; Goldowitz, Daniel; Guler, Reto; Ha, Thomas; Hara, Mitsuko; Herlyn, Meenhard; Ikawa, Tomokatsu; Kai, Chieko; Kawamoto, Hiroshi; Khachigian, Levon M.; Klinken, S. Peter; Kojima, Soichi; Koseki, Haruhiko; Klein, Sarah; Mejhert, Niklas; Miyaguchi, Ken; Mizuno, Yosuke; Morimoto, Mitsuru; Morris, Kelly J.; Mummery, Christine; Nakachi, Yutaka; Ogishima, Soichi; Okada-Hatakeyama, Mariko; Okazaki, Yasushi; Orlando, Valerio; Ovchinnikov, Dmitry; Passier, Robert; Patrikakis, Margaret; Pombo, Ana; Qin, Xian-Yang; Roy, Sugata; Sato, Hiroki; Savvi, Suzana; Saxena, Alka; Schwegmann, Anita; Sugiyama, Daisuke; Swoboda, Rolf; Tanaka, Hiroshi; Tomoiu, Andru; Winteringham, Louise N.; Wolvetang, Ernst; Yanagi-Mizuochi, Chiyo; Yoneda, Misako; Zabierowski, Susan; Zhang, Peter; Abugessaisa, Imad; Bertin, Nicolas; Diehl, Alexander D.; Fukuda, Shiro; Furuno, Masaaki; Harshbarger, Jayson; Hasegawa, Akira; Hori, Fumi; Ishikawa-Kato, Sachi; Ishizu, Yuri; Itoh, Masayoshi; Kawashima, Tsugumi; Kojima, Miki; Kondo, Naoto; Lizio, Marina; Meehan, Terrence F.; Mungall, Christopher J.; Murata, Mitsuyoshi; Nishiyori-Sueki, Hiromi; Sahin, Serkan; Nagao-Sato, Sayaka; Severin, Jessica; de Hoon, Michiel J. L.; Kawai, Jun; Kasukawa, Takeya; Lassmann, Timo; Suzuki, Harukazu; Kawaji, Hideya; Summers, Kim M.; Wells, Christine; Hume, David A.; Forrest, Alistair R. R.; Sandelin, Albin; Carninci, Piero; Hayashizaki, Yoshihide

    2015-01-01

    Although it is generally accepted that cellular differentiation requires changes to transcriptional networks, dynamic regulation of promoters and enhancers at specific sets of genes has not been previously studied en masse. Exploiting the fact that active promoters and enhancers are transcribed, we simultaneously measured their activity in 19 human and 14 mouse time courses covering a wide range of cell types and biological stimuli. Enhancer RNAs, then messenger RNAs encoding transcription factors, dominated the earliest responses. Binding sites for key lineage transcription factors were simultaneously overrepresented in enhancers and promoters active in each cellular system. Our data support a highly generalizable model in which enhancer transcription is the earliest event in successive waves of transcriptional change during cellular differentiation or activation. PMID:25678556

  13. Negative autoregulation matches production and demand in synthetic transcriptional networks.

    Science.gov (United States)

    Franco, Elisa; Giordano, Giulia; Forsberg, Per-Ola; Murray, Richard M

    2014-08-15

    We propose a negative feedback architecture that regulates activity of artificial genes, or "genelets", to meet their output downstream demand, achieving robustness with respect to uncertain open-loop output production rates. In particular, we consider the case where the outputs of two genelets interact to form a single assembled product. We show with analysis and experiments that negative autoregulation matches the production and demand of the outputs: the magnitude of the regulatory signal is proportional to the "error" between the circuit output concentration and its actual demand. This two-device system is experimentally implemented using in vitro transcriptional networks, where reactions are systematically designed by optimizing nucleic acid sequences with publicly available software packages. We build a predictive ordinary differential equation (ODE) model that captures the dynamics of the system and can be used to numerically assess the scalability of this architecture to larger sets of interconnected genes. Finally, with numerical simulations we contrast our negative autoregulation scheme with a cross-activation architecture, which is less scalable and results in slower response times.

  14. Intrinsic Disorder in Male Sex Determination: Disorderedness of Proteins from the Sry Transcriptional Network.

    Science.gov (United States)

    Merone, Jean; Nwogu, Onyekahi; Redington, Jennifer M; Uversky, Vladimir N

    2016-10-28

    Sex differentiation is a complex process where sexually indifferent embryo progressively acquires male or female characteristics via tightly controlled, perfectly timed, and sophisticatedly intertwined chain of events. This process is controlled and regulated by a set of specific proteins, with one of the first steps in sex differentiation being the activation of the Y-chromosomal Sry gene (sex-determining region Y) in males that acts as a switch from undifferentiated gonad somatic cells to testis development. There are several key players in this process, which constitute the Sry transcriptional network, and collective action of which governs testis determination. Although it is accepted now that many proteins engaged in signal transduction as well as regulation and control of various biological processes are intrinsically disordered (i.e., do not have unique structure and remain unstructured, or incompletely structured, under physiological conditions), the roles and profusion of intrinsic disorder in proteins involved in the male sex determination have not been accessed as of yet. The goal of this study is to cover this gap by analyzing some key players of the Sry transcriptional network. To this end, we employed a broad set of computational tools for intrinsic disorder analysis and conducted intensive literature search in order to gain information on the structural peculiarities of the Sry network-related proteins, their intrinsic disorder predispositions, and the roles of intrinsic disorder in their functions.

  15. The cell cycle rallies the transcription cycle: Cdc28/Cdk1 is a cell cycle-regulated transcriptional CDK.

    Science.gov (United States)

    Chymkowitch, Pierre; Enserink, Jorrit M

    2013-01-01

    In the budding yeast Saccharomyces cerevisiae, the cyclin-dependent kinases (CDKs) Kin28, Bur1 and Ctk1 regulate basal transcription by phosphorylating the carboxyl-terminal domain (CTD) of RNA polymerase II. However, very little is known about the involvement of the cell cycle CDK Cdc28 in the transcription process. We have recently shown that, upon cell cycle entry, Cdc28 kinase activity boosts transcription of a subset of genes by directly stimulating the basal transcription machinery. Here, we discuss the biological significance of this finding and give our view of the kinase-dependent role of Cdc28 in regulation of RNA polymerase II.

  16. Dynamic transcription factor activity and networks during ErbB2 breast oncogenesis and targeted therapy.

    Science.gov (United States)

    Weiss, M S; Peñalver Bernabé, B; Shin, S; Asztalos, S; Dubbury, S J; Mui, M D; Bellis, A D; Bluver, D; Tonetti, D A; Saez-Rodriguez, J; Broadbelt, L J; Jeruss, J S; Shea, L D

    2014-12-01

    Tissue development and disease progression are multi-stage processes controlled by an evolving set of key regulatory factors, and identifying these factors necessitates a dynamic analysis spanning relevant time scales. Current omics approaches depend on incomplete biological databases to identify critical cellular processes. Herein, we present TRACER (TRanscriptional Activity CEll aRrays), which was employed to quantify the dynamic activity of numerous transcription factor (TFs) simultaneously in 3D and networks for TRACER (NTRACER), a computational algorithm that allows for cellular rewiring to establish dynamic regulatory networks based on activity of TF reporter constructs. We identified major hubs at various stages of culture associated with normal and abnormal tissue growth (i.e., ELK-1 and E2F1, respectively) and the mechanism of action for a targeted therapeutic, lapatinib, through GATA-1, which were confirmed in human ErbB2 positive breast cancer patients and human ErbB2 positive breast cancer cell lines that were either sensitive or resistant to lapatinib.

  17. Functional interactions among members of the MAX and MLX transcriptional network during oncogenesis.

    Science.gov (United States)

    Diolaiti, Daniel; McFerrin, Lisa; Carroll, Patrick A; Eisenman, Robert N

    2015-05-01

    The transcription factor MYC and its related family members MYCN and MYCL have been implicated in the etiology of a wide spectrum of human cancers. Compared to other oncoproteins, such as RAS or SRC, MYC is unique because its protein coding region is rarely mutated. Instead, MYC's oncogenic properties are unleashed by regulatory mutations leading to unconstrained high levels of expression. Under both normal and pathological conditions MYC regulates multiple aspects of cellular physiology including proliferation, differentiation, apoptosis, growth and metabolism by controlling the expression of thousands of genes. How a single transcription factor exerts such broad effects remains a fascinating puzzle. Notably, MYC is part of a network of bHLHLZ proteins centered on the MYC heterodimeric partner MAX and its counterpart, the MAX-like protein MLX. This network includes MXD1-4, MNT, MGA, MONDOA and MONDOB proteins. With some exceptions, MXD proteins have been functionally linked to cell cycle arrest and differentiation, while MONDO proteins control cellular metabolism. Although the temporal expression patterns of many of these proteins can differ markedly they are frequently expressed simultaneously in the same cellular context, and potentially bind to the same, or similar DNA consensus sequence. Here we review the activities and interactions among these proteins and propose that the broad spectrum of phenotypes elicited by MYC deregulation is intimately connected to the functions and regulation of the other network members. Furthermore, we provide a meta-analysis of TCGA data suggesting that the coordinate regulation of the network is important in MYC driven tumorigenesis. This article is part of a Special Issue entitled: Myc proteins in cell biology and pathology.

  18. MicroRNA and transcription factor mediated regulatory network for ovarian cancer: regulatory network of ovarian cancer.

    Science.gov (United States)

    Ying, Huanchun; Lv, Jing; Ying, Tianshu; Li, Jun; Yang, Qing; Ma, Yuan

    2013-10-01

    A better understanding on the regulatory interactions of microRNA (miRNA) target genes and transcription factor (TF) target genes in ovarian cancer may be conducive for developing early diagnosis strategy. Thus, gene expression data and miRNA expression data were downloaded from The Cancer Genome Atlas in this study. Differentially expressed genes and miRNAs were selected out with t test, and Gene Ontology enrichment analysis was performed with DAVID tools. Regulatory interactions were retrieved from miRTarBase, TRED, and TRANSFAC, and then networks for miRNA target genes and TF target genes were constructed to globally present the mechanisms. As a result, a total of 1,939 differentially expressed genes were identified, and they were enriched in 28 functions, among which cell cycle was affected to the most degree. Besides, 213 differentially expressed miRNAs were identified. Two regulatory networks for miRNA target genes and TF target genes were established and then both were combined, in which E2F transcription factor 1, cyclin-dependent kinase inhibitor 1A, cyclin E1, and miR-16 were the hub genes. These genes may be potential biomarkers for ovarian cancer.

  19. RAD21 cooperates with pluripotency transcription factors in the maintenance of embryonic stem cell identity.

    Directory of Open Access Journals (Sweden)

    Anja Nitzsche

    Full Text Available For self-renewal, embryonic stem cells (ESCs require the expression of specific transcription factors accompanied by a particular chromosome organization to maintain a balance between pluripotency and the capacity for rapid differentiation. However, how transcriptional regulation is linked to chromosome organization in ESCs is not well understood. Here we show that the cohesin component RAD21 exhibits a functional role in maintaining ESC identity through association with the pluripotency transcriptional network. ChIP-seq analyses of RAD21 reveal an ESC specific cohesin binding pattern that is characterized by CTCF independent co-localization of cohesin with pluripotency related transcription factors Oct4, Nanog, Sox2, Esrrb and Klf4. Upon ESC differentiation, most of these binding sites disappear and instead new CTCF independent RAD21 binding sites emerge, which are enriched for binding sites of transcription factors implicated in early differentiation. Furthermore, knock-down of RAD21 causes expression changes that are similar to expression changes after Nanog depletion, demonstrating the functional relevance of the RAD21--pluripotency transcriptional network association. Finally, we show that Nanog physically interacts with the cohesin or cohesin interacting proteins STAG1 and WAPL further substantiating this association. Based on these findings we propose that a dynamic placement of cohesin by pluripotency transcription factors contributes to a chromosome organization supporting the ESC expression program.

  20. Ligand-specific sequential regulation of transcription factors for differentiation of MCF-7 cells

    Directory of Open Access Journals (Sweden)

    Toyoda Tetsuro

    2009-11-01

    Full Text Available Abstract Background Sharing a common ErbB/HER receptor signaling pathway, heregulin (HRG induces differentiation of MCF-7 human breast cancer cells while epidermal growth factor (EGF elicits proliferation. Although cell fates resulting from action of the aforementioned ligands completely different, the respective gene expression profiles in early transcription are qualitatively similar, suggesting that gene expression during late transcription, but not early transcription, may reflect ligand specificity. In this study, based on both the data from time-course quantitative real-time PCR on over 2,000 human transcription factors and microarray of all human genes, we identified a series of transcription factors which may control HRG-specific late transcription in MCF-7 cells. Results We predicted that four transcription factors including EGR4, FRA-1, FHL2, and DIPA should have responsibility of regulation in MCF-7 cell differentiation. Validation analysis suggested that one member of the activator protein 1 (AP-1 family, FOSL-1 (FRA-1 gene, appeared immediately following c-FOS expression, might be responsible for expression of transcription factor FHL2 through activation of the AP-1 complex. Furthermore, RNAi gene silencing of FOSL-1 and FHL2 resulted in increase of extracellular signal-regulated kinase (ERK phosphorylation of which duration was sustained by HRG stimulation. Conclusion Our analysis indicated that a time-dependent transcriptional regulatory network including c-FOS, FRA-1, and FHL2 is vital in controlling the ERK signaling pathway through a negative feedback loop for MCF-7 cell differentiation.

  1. Transcriptional and post-transcriptional regulation of nucleotide excision repair genes in human cells

    Energy Technology Data Exchange (ETDEWEB)

    Lefkofsky, Hailey B. [Translational Oncology Program, University of Michigan Medical School, Ann Arbor, MI (United States); Veloso, Artur [Translational Oncology Program, University of Michigan Medical School, Ann Arbor, MI (United States); Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Bioinformatics Program, Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI (United States); Ljungman, Mats, E-mail: ljungman@umich.edu [Translational Oncology Program, University of Michigan Medical School, Ann Arbor, MI (United States); Department of Radiation Oncology, University of Michigan Medical School, Ann Arbor, MI (United States); Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI (United States)

    2015-06-15

    Nucleotide excision repair (NER) removes DNA helix-distorting lesions induced by UV light and various chemotherapeutic agents such as cisplatin. These lesions efficiently block the elongation of transcription and need to be rapidly removed by transcription-coupled NER (TC-NER) to avoid the induction of apoptosis. Twenty-nine genes have been classified to code for proteins participating in nucleotide excision repair (NER) in human cells. Here we explored the transcriptional and post-transcriptional regulation of these NER genes across 13 human cell lines using Bru-seq and BruChase-seq, respectively. Many NER genes are relatively large in size and therefore will be easily inactivated by UV-induced transcription-blocking lesions. Furthermore, many of these genes produce transcripts that are rather unstable. Thus, these genes are expected to rapidly lose expression leading to a diminished function of NER. One such gene is ERCC6 that codes for the CSB protein critical for TC-NER. Due to its large gene size and high RNA turnover rate, the ERCC6 gene may act as dosimeter of DNA damage so that at high levels of damage, ERCC6 RNA levels would be diminished leading to the loss of CSB expression, inhibition of TC-NER and the promotion of cell death.

  2. Data integration for identification of important transcription factors of STAT6-mediated cell fate decisions.

    Science.gov (United States)

    Jargosch, M; Kröger, S; Gralinska, E; Klotz, U; Fang, Z; Chen, W; Leser, U; Selbig, J; Groth, D; Baumgrass, R

    2016-06-24

    Data integration has become a useful strategy for uncovering new insights into complex biological networks. We studied whether this approach can help to delineate the signal transducer and activator of transcription 6 (STAT6)-mediated transcriptional network driving T helper (Th) 2 cell fate decisions. To this end, we performed an integrative analysis of publicly available RNA-seq data of Stat6-knockout mouse studies together with STAT6 ChIP-seq data and our own gene expression time series data during Th2 cell differentiation. We focused on transcription factors (TFs), cytokines, and cytokine receptors and delineated 59 positively and 41 negatively STAT6-regulated genes, which were used to construct a transcriptional network around STAT6. The network illustrates that important and well-known TFs for Th2 cell differentiation are positively regulated by STAT6 and act either as activators for Th2 cells (e.g., Gata3, Atf3, Satb1, Nfil3, Maf, and Pparg) or as suppressors for other Th cell subpopulations such as Th1 (e.g., Ar), Th17 (e.g., Etv6), or iTreg (e.g., Stat3 and Hif1a) cells. Moreover, our approach reveals 11 TFs (e.g., Atf5, Creb3l2, and Asb2) with unknown functions in Th cell differentiation. This fact together with the observed enrichment of asthma risk genes among those regulated by STAT6 underlines the potential value of the data integration strategy used here. Thus, our results clearly support the opinion that data integration is a useful tool to delineate complex physiological processes.

  3. Modeling transcriptional networks regulating secondary growth and wood formation in forest trees.

    Science.gov (United States)

    Liu, Lijun; Filkov, Vladimir; Groover, Andrew

    2014-06-01

    The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary growth), but a comprehensive understanding of how these genes interact to influence woody growth is currently lacking. Modeling transcriptional networks has recently been made tractable by next-generation sequencing-based technologies that can comprehensively catalog gene expression and transcription factor-binding genome-wide, but has not yet been extensively applied to undomesticated tree species or woody growth. Here we discuss basic features of transcriptional networks, approaches for modeling biological networks, and examples of biological network models developed for forest trees to date. We discuss how transcriptional network research is being developed in the model forest tree genus, Populus, and how this research area can be further developed and applied. Transcriptional network models for forest tree secondary growth and wood formation could ultimately provide new predictive models to accelerate hypothesis-driven research and develop new breeding applications.

  4. A sticky situation: untangling the transcriptional network controlling biofilm development in Candida albicans.

    Science.gov (United States)

    Fox, Emily P; Nobile, Clarissa J

    2012-01-01

    Candida albicans is a commensal microorganism of the human microbiome; it is also the most prevalent fungal pathogen of humans. Many infections caused by C. albicans are a direct consequence of its proclivity to form biofilms--resilient, surface-associated communities of cells where individual cells acquire specialized properties that are distinct from those observed in suspension cultures. We recently identified the transcriptional network that orchestrates the formation of biofilms in C. albicans. These results set the stage for understanding how biofilms are formed and, once formed, how the specialized properties of biofilms are elaborated. This information will provide new insight for understanding biofilms in more detail and may lead to improvements in preventing and treating biofilm-based infections in the future.

  5. Establishing and maintaining the Langerhans cell network.

    Science.gov (United States)

    Chopin, Michaël; Nutt, Stephen L

    2015-05-01

    Langerhans cells (LCs) are the unique antigen-presenting cell of the epidermis. LCs have long been depicted in textbooks as the archetypical dendritic cell that alerts the immune system upon pathogen induced skin barrier breakage, however recent findings argue instead for a more tolerogenic function. While the LCs that populate the epidermis in steady-state arise from progenitors that seed the skin during embryogenesis, it is now apparent that a second pathway generating LCs from a bone marrow derived progenitor is active in inflammatory settings. This review emphasizes the determinants underpinning the establishment of the LC network in steady-state and under inflammatory conditions, as well as the transcriptional machinery governing their differentiation. The dual origin of LCs raises important questions about the functional differences between these subsets in balancing the epidermal immune response between immunity and tolerance.

  6. PPARα Promotes Cancer Cell Glut1 Transcription Repression.

    Science.gov (United States)

    You, Mengli; Jin, Jianhua; Liu, Qian; Xu, QingGang; Shi, Juanjuan; Hou, Yongzhong

    2017-06-01

    Abundant nutrient availability including glucose and amino acids plays an important role in maintaining cancer cell energetic and biosynthetic pathways. As a nuclear receptor, peroxisome-proliferator-activated receptor α (PPARα) regulates inflammation and cancer progression, however, it is still unclear the interaction of PPARα with the cancer cell glucose metabolism. Here we found that PPARα reduced Glut1 (Glucose transporter 1) protein and gene levels in HCT-116, SW480, HeLa, and MCF-7 cancer cell lines. In contrast, silenced PPARα reversed this event. Further analysis shows that PPARα directly targeted the consensus PPRE motif of Glut1 promoter region resulting in Glut1 transcription repression. PPARα-mediated Glut1 transcription repression led to decreased influx of glucose in cancer cells. These findings revealed a novel mechanism of PPARα-mediated cancer cell Glut1 transcription repression. J. Cell. Biochem. 118: 1556-1562, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  7. In Silico Identification of Co-transcribed Core Cell Cycle Regulators and Transcription Factors in Arabidopsis

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Regulatory networks involving transcription factors and core cell cycle regulators are expected to play crucial roles in plant growth and development. In this report, we describe the identification of two groups of co-transcribed core cell cycle regulators and transcription factors via a two-step in silico screening. The core cell cycle regulators include TARDY ASYNCHRONOUS MEIOSIS (CYCA1;2), CYCB1;1, CYCB2;1, CDKB1;2, and CDKB2;2 while the transcription factors include CURLY LEAF, AINTEGUMENTA, a MYB protein, two Forkhead-associated domain proteins, and a SCARECROW family protein. Promoter analysis revealed a potential web of cross- and self-regulations among the identified proteins. Because one criterion for screening for these genes is that they are predominantly transcribed in young organs but not in mature organs, these genes are likely to be particularly involved in Arabidopsis organ growth.

  8. Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

    Science.gov (United States)

    Siletz, Anaar; Schnabel, Michael; Kniazeva, Ekaterina; Schumacher, Andrew J; Shin, Seungjin; Jeruss, Jacqueline S; Shea, Lonnie D

    2013-01-01

    The epithelial-mesenchymal transition (EMT) is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs) are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

  9. Dynamic transcription factor networks in epithelial-mesenchymal transition in breast cancer models.

    Directory of Open Access Journals (Sweden)

    Anaar Siletz

    Full Text Available The epithelial-mesenchymal transition (EMT is a complex change in cell differentiation that allows breast carcinoma cells to acquire invasive properties. EMT involves a cascade of regulatory changes that destabilize the epithelial phenotype and allow mesenchymal features to manifest. As transcription factors (TFs are upstream effectors of the genome-wide expression changes that result in phenotypic change, understanding the sequential changes in TF activity during EMT provides rich information on the mechanism of this process. Because molecular interactions will vary as cells progress from an epithelial to a mesenchymal differentiation program, dynamic networks are needed to capture the changing context of molecular processes. In this study we applied an emerging high-throughput, dynamic TF activity array to define TF activity network changes in three cell-based models of EMT in breast cancer based on HMLE Twist ER and MCF-7 mammary epithelial cells. The TF array distinguished conserved from model-specific TF activity changes in the three models. Time-dependent data was used to identify pairs of TF activities with significant positive or negative correlation, indicative of interdependent TF activity throughout the six-day study period. Dynamic TF activity patterns were clustered into groups of TFs that change along a time course of gene expression changes and acquisition of invasive capacity. Time-dependent TF activity data was combined with prior knowledge of TF interactions to construct dynamic models of TF activity networks as epithelial cells acquire invasive characteristics. These analyses show EMT from a unique and targetable vantage and may ultimately contribute to diagnosis and therapy.

  10. Human population-specific gene expression and transcriptional network modification with polymorphic transposable elements.

    Science.gov (United States)

    Wang, Lu; Rishishwar, Lavanya; Mariño-Ramírez, Leonardo; Jordan, I King

    2016-12-19

    Transposable element (TE) derived sequences are known to contribute to the regulation of the human genome. The majority of known TE-derived regulatory sequences correspond to relatively ancient insertions, which are fixed across human populations. The extent to which human genetic variation caused by recent TE activity leads to regulatory polymorphisms among populations has yet to be thoroughly explored. In this study, we searched for associations between polymorphic TE (polyTE) loci and human gene expression levels using an expression quantitative trait loci (eQTL) approach. We compared locus-specific polyTE insertion genotypes to B cell gene expression levels among 445 individuals from 5 human populations. Numerous human polyTE loci correspond to both cis and trans eQTL, and their regulatory effects are directly related to cell type-specific function in the immune system. PolyTE loci are associated with differences in expression between European and African population groups, and a single polyTE loci is indirectly associated with the expression of numerous genes via the regulation of the B cell-specific transcription factor PAX5 The polyTE-gene expression associations we found indicate that human TE genetic variation can have important phenotypic consequences. Our results reveal that TE-eQTL are involved in population-specific gene regulation as well as transcriptional network modification.

  11. Human population-specific gene expression and transcriptional network modification with polymorphic transposable elements

    Science.gov (United States)

    Wang, Lu; Mariño-Ramírez, Leonardo

    2017-01-01

    Abstract Transposable element (TE) derived sequences are known to contribute to the regulation of the human genome. The majority of known TE-derived regulatory sequences correspond to relatively ancient insertions, which are fixed across human populations. The extent to which human genetic variation caused by recent TE activity leads to regulatory polymorphisms among populations has yet to be thoroughly explored. In this study, we searched for associations between polymorphic TE (polyTE) loci and human gene expression levels using an expression quantitative trait loci (eQTL) approach. We compared locus-specific polyTE insertion genotypes to B cell gene expression levels among 445 individuals from 5 human populations. Numerous human polyTE loci correspond to both cis and trans eQTL, and their regulatory effects are directly related to cell type-specific function in the immune system. PolyTE loci are associated with differences in expression between European and African population groups, and a single polyTE loci is indirectly associated with the expression of numerous genes via the regulation of the B cell-specific transcription factor PAX5. The polyTE-gene expression associations we found indicate that human TE genetic variation can have important phenotypic consequences. Our results reveal that TE-eQTL are involved in population-specific gene regulation as well as transcriptional network modification. PMID:27998931

  12. SoxB1-driven transcriptional network underlies neural-specific interpretation of morphogen signals.

    Science.gov (United States)

    Oosterveen, Tony; Kurdija, Sanja; Ensterö, Mats; Uhde, Christopher W; Bergsland, Maria; Sandberg, Magnus; Sandberg, Rickard; Muhr, Jonas; Ericson, Johan

    2013-04-30

    The reiterative deployment of a small cadre of morphogen signals underlies patterning and growth of most tissues during embyogenesis, but how such inductive events result in tissue-specific responses remains poorly understood. By characterizing cis-regulatory modules (CRMs) associated with genes regulated by Sonic hedgehog (Shh), retinoids, or bone morphogenetic proteins in the CNS, we provide evidence that the neural-specific interpretation of morphogen signaling reflects a direct integration of these pathways with SoxB1 proteins at the CRM level. Moreover, expression of SoxB1 proteins in the limb bud confers on mesodermal cells the potential to activate neural-specific target genes upon Shh, retinoid, or bone morphogenetic protein signaling, and the collocation of binding sites for SoxB1 and morphogen-mediatory transcription factors in CRMs faithfully predicts neural-specific gene activity. Thus, an unexpectedly simple transcriptional paradigm appears to conceptually explain the neural-specific interpretation of pleiotropic signaling during vertebrate development. Importantly, genes induced in a SoxB1-dependent manner appear to constitute repressive gene regulatory networks that are directly interlinked at the CRM level to constrain the regional expression of patterning genes. Accordingly, not only does the topology of SoxB1-driven gene regulatory networks provide a tissue-specific mode of gene activation, but it also determines the spatial expression pattern of target genes within the developing neural tube.

  13. Dataset of transcriptional landscape of B cell early activation

    Directory of Open Access Journals (Sweden)

    Alexander S. Garruss

    2015-09-01

    Full Text Available Signaling via B cell receptors (BCR and Toll-like receptors (TLRs result in activation of B cells with distinct physiological outcomes, but transcriptional regulatory mechanisms that drive activation and distinguish these pathways remain unknown. At early time points after BCR and TLR ligand exposure, 0.5 and 2 h, RNA-seq was performed allowing observations on rapid transcriptional changes. At 2 h, ChIP-seq was performed to allow observations on important regulatory mechanisms potentially driving transcriptional change. The dataset includes RNA-seq, ChIP-seq of control (Input, RNA Pol II, H3K4me3, H3K27me3, and a separate RNA-seq for miRNA expression, which can be found at Gene Expression Omnibus Dataset GSE61608. Here, we provide details on the experimental and analysis methods used to obtain and analyze this dataset and to examine the transcriptional landscape of B cell early activation.

  14. Small molecule selectively suppresses MYC transcription in cancer cells.

    Science.gov (United States)

    Bouvard, Claire; Lim, Sang Min; Ludka, John; Yazdani, Nahid; Woods, Ashley K; Chatterjee, Arnab K; Schultz, Peter G; Zhu, Shoutian

    2017-03-28

    Stauprimide is a staurosporine analog that promotes embryonic stem cell (ESC) differentiation by inhibiting nuclear localization of the MYC transcription factor NME2, which in turn results in down-regulation of MYC transcription. Given the critical role the oncogene MYC plays in tumor initiation and maintenance, we explored the potential of stauprimide as an anticancer agent. Here we report that stauprimide suppresses MYC transcription in cancer cell lines derived from distinct tissues. Using renal cancer cells, we confirmed that stauprimide inhibits NME2 nuclear localization. Gene expression analysis also confirmed the selective down-regulation of MYC target genes by stauprimide. Consistent with this activity, administration of stauprimide inhibited tumor growth in rodent xenograft models. Our study provides a unique strategy for selectively targeting MYC transcription by pharmacological means as a potential treatment for MYC-dependent tumors.

  15. A guide to integrating transcriptional regulatory and metabolic networks using PROM (probabilistic regulation of metabolism).

    Science.gov (United States)

    Simeonidis, Evangelos; Chandrasekaran, Sriram; Price, Nathan D

    2013-01-01

    The integration of transcriptional regulatory and metabolic networks is a crucial step in the process of predicting metabolic behaviors that emerge from either genetic or environmental changes. Here, we present a guide to PROM (probabilistic regulation of metabolism), an automated method for the construction and simulation of integrated metabolic and transcriptional regulatory networks that enables large-scale phenotypic predictions for a wide range of model organisms.

  16. Deciphering Fur transcriptional regulatory network highlights its complex role beyond iron metabolism in Escherichia coli

    DEFF Research Database (Denmark)

    Seo, Sang Woo; Kim, Donghyuk; Latif, Haythem;

    2014-01-01

    The ferric uptake regulator (Fur) plays a critical role in the transcriptional regulation of iron metabolism. However, the full regulatory potential of Fur remains undefined. Here we comprehensively reconstruct the Fur transcriptional regulatory network in Escherichia coli K-12 MG1655 in response...

  17. Cell cycle-dependent gene networks relevant to cancer

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The analysis of sophisticated interplays between cell cycle-dependent genes in a disease condition is one of the largely unexplored areas in modern tumor biology research. Many cell cycle-dependent genes are either oncogenes or suppressor genes, or are closely asso- ciated with the transition of a cell cycle. However, it is unclear how the complicated relationships between these cell cycle-dependent genes are, especially in cancers. Here, we sought to identify significant expression relationships between cell cycle-dependent genes by analyzing a HeLa microarray dataset using a local alignment algorithm and constructed a gene transcriptional network specific to the cancer by assembling these newly identified gene-gene relationships. We further characterized this global network by partitioning the whole network into several cell cycle phase-specific sub-networks. All generated networks exhibited the power-law node-degree dis- tribution, and the average clustering coefficients of these networks were remarkably higher than those of pure scale-free networks, indi- cating a property of hierarchical modularity. Based on the known protein-protein interactions and Gene Ontology annotation data, the proteins encoded by cell cycle-dependent interacting genes tended to share the same biological functions or to be involved in the same biological processes, rather than interacting by physical means. Finally, we identified the hub genes related to cancer based on the topo- logical importance that maintain the basic structure of cell cycle-dependent gene networks.

  18. Research resource: the dynamic transcriptional profile of sertoli cells during the progression of spermatogenesis.

    Science.gov (United States)

    Zimmermann, Céline; Stévant, Isabelle; Borel, Christelle; Conne, Béatrice; Pitetti, Jean-Luc; Calvel, Pierre; Kaessmann, Henrik; Jégou, Bernard; Chalmel, Frédéric; Nef, Serge

    2015-04-01

    Sertoli cells (SCs), the only somatic cells within seminiferous tubules, associate intimately with developing germ cells. They not only provide physical and nutritional support but also secrete factors essential to the complex developmental processes of germ cell proliferation and differentiation. The SC transcriptome must therefore adapt rapidly during the different stages of spermatogenesis. We report comprehensive genome-wide expression profiles of pure populations of SCs isolated at 5 distinct stages of the first wave of mouse spermatogenesis, using RNA sequencing technology. We were able to reconstruct about 13 901 high-confidence, nonredundant coding and noncoding transcripts, characterized by complex alternative splicing patterns with more than 45% comprising novel isoforms of known genes. Interestingly, roughly one-fifth (2939) of these genes exhibited a dynamic expression profile reflecting the evolving role of SCs during the progression of spermatogenesis, with stage-specific expression of genes involved in biological processes such as cell cycle regulation, metabolism and energy production, retinoic acid synthesis, and blood-testis barrier biogenesis. Finally, regulatory network analysis identified the transcription factors endothelial PAS domain-containing protein 1 (EPAS1/Hif2α), aryl hydrocarbon receptor nuclear translocator (ARNT/Hif1β), and signal transducer and activator of transcription 1 (STAT1) as potential master regulators driving the SC transcriptional program. Our results highlight the plastic transcriptional landscape of SCs during the progression of spermatogenesis and provide valuable resources to better understand SC function and spermatogenesis and its related disorders, such as male infertility.

  19. DriverNet: uncovering the impact of somatic driver mutations on transcriptional networks in cancer.

    Science.gov (United States)

    Bashashati, Ali; Haffari, Gholamreza; Ding, Jiarui; Ha, Gavin; Lui, Kenneth; Rosner, Jamie; Huntsman, David G; Caldas, Carlos; Aparicio, Samuel A; Shah, Sohrab P

    2012-12-22

    Simultaneous interrogation of tumor genomes and transcriptomes is underway in unprecedented global efforts. Yet, despite the essential need to separate driver mutations modulating gene expression networks from transcriptionally inert passenger mutations, robust computational methods to ascertain the impact of individual mutations on transcriptional networks are underdeveloped. We introduce a novel computational framework, DriverNet, to identify likely driver mutations by virtue of their effect on mRNA expression networks. Application to four cancer datasets reveals the prevalence of rare candidate driver mutations associated with disrupted transcriptional networks and a simultaneous modulation of oncogenic and metabolic networks, induced by copy number co-modification of adjacent oncogenic and metabolic drivers. DriverNet is available on Bioconductor or at http://compbio.bccrc.ca/software/drivernet/.

  20. An environment-dependent transcriptional network specifies human microglia identity

    NARCIS (Netherlands)

    Gosselin, David; Skola, Dylan; Coufal, Nicole G.; Holtman, Inge R.; Schlachetzki, Johannes C. M.; Sajti, Eniko; Jaeger, Baptiste N.; O'Connor, Carolyn; Fitzpatrick, Conor; Pasillas, Martina P.; Pena, Monique; Adair, Amy; Gonda, David D.; Levy, Michael L.; Ransohoff, Richard M.; Gage, Fred H.; Glass, Christopher K.

    2017-01-01

    Microglia play essential roles in central nervous system (CNS) homeostasis and influence diverse aspects of neuronal function. However, the transcriptional mechanisms that specify human microglia phenotypes are largely unknown. We examined the transcriptomes and epigenetic landscapes of human microg

  1. Transcriptional network inference from functional similarity and expression data: a global supervised approach.

    Science.gov (United States)

    Ambroise, Jérôme; Robert, Annie; Macq, Benoit; Gala, Jean-Luc

    2012-01-06

    An important challenge in system biology is the inference of biological networks from postgenomic data. Among these biological networks, a gene transcriptional regulatory network focuses on interactions existing between transcription factors (TFs) and and their corresponding target genes. A large number of reverse engineering algorithms were proposed to infer such networks from gene expression profiles, but most current methods have relatively low predictive performances. In this paper, we introduce the novel TNIFSED method (Transcriptional Network Inference from Functional Similarity and Expression Data), that infers a transcriptional network from the integration of correlations and partial correlations of gene expression profiles and gene functional similarities through a supervised classifier. In the current work, TNIFSED was applied to predict the transcriptional network in Escherichia coli and in Saccharomyces cerevisiae, using datasets of 445 and 170 affymetrix arrays, respectively. Using the area under the curve of the receiver operating characteristics and the F-measure as indicators, we showed the predictive performance of TNIFSED to be better than unsupervised state-of-the-art methods. TNIFSED performed slightly worse than the supervised SIRENE algorithm for the target genes identification of the TF having a wide range of yet identified target genes but better for TF having only few identified target genes. Our results indicate that TNIFSED is complementary to the SIRENE algorithm, and particularly suitable to discover target genes of "orphan" TFs.

  2. Identification of cross-species shared transcriptional networks of diabetic nephropathy in human and mouse glomeruli.

    Science.gov (United States)

    Hodgin, Jeffrey B; Nair, Viji; Zhang, Hongyu; Randolph, Ann; Harris, Raymond C; Nelson, Robert G; Weil, E Jennifer; Cavalcoli, James D; Patel, Jignesh M; Brosius, Frank C; Kretzler, Matthias

    2013-01-01

    Murine models are valuable instruments in defining the pathogenesis of diabetic nephropathy (DN), but they only partially recapitulate disease manifestations of human DN, limiting their utility. To define the molecular similarities and differences between human and murine DN, we performed a cross-species comparison of glomerular transcriptional networks. Glomerular gene expression was profiled in patients with early type 2 DN and in three mouse models (streptozotocin DBA/2, C57BLKS db/db, and eNOS-deficient C57BLKS db/db mice). Species-specific transcriptional networks were generated and compared with a novel network-matching algorithm. Three shared human-mouse cross-species glomerular transcriptional networks containing 143 (Human-DBA STZ), 97 (Human-BKS db/db), and 162 (Human-BKS eNOS(-/-) db/db) gene nodes were generated. Shared nodes across all networks reflected established pathogenic mechanisms of diabetes complications, such as elements of Janus kinase (JAK)/signal transducer and activator of transcription (STAT) and vascular endothelial growth factor receptor (VEGFR) signaling pathways. In addition, novel pathways not previously associated with DN and cross-species gene nodes and pathways unique to each of the human-mouse networks were discovered. The human-mouse shared glomerular transcriptional networks will assist DN researchers in selecting mouse models most relevant to the human disease process of interest. Moreover, they will allow identification of new pathways shared between mice and humans.

  3. C/EBPβ regulates transcription factors critical for proliferation and survival of multiple myeloma cells

    Science.gov (United States)

    Pal, Rekha; Janz, Martin; Galson, Deborah L.; Gries, Margarete; Li, Shirong; Jöhrens, Korinna; Anagnostopoulos, Ioannis; Dörken, Bernd; Mapara, Markus Y.; Borghesi, Lisa; Kardava, Lela; Roodman, G. David; Milcarek, Christine

    2009-01-01

    CCAAT/enhancer-binding protein β (C/EBPβ), also known as nuclear factor–interleukin-6 (NF-IL6), is a transcription factor that plays an important role in the regulation of growth and differentiation of myeloid and lymphoid cells. Mice deficient in C/EBPβ show impaired generation of B lymphocytes. We show that C/EBPβ regulates transcription factors critical for proliferation and survival in multiple myeloma. Multiple myeloma cell lines and primary multiple myeloma cells strongly expressed C/EBPβ, whereas normal B cells and plasma cells had little or no detectable levels of C/EBPβ. Silencing of C/EBPβ led to down-regulation of transcription factors such as IRF4, XBP1, and BLIMP1 accompanied by a strong inhibition of proliferation. Further, silencing of C/EBPβ led to a complete down-regulation of antiapoptotic B-cell lymphoma 2 (BCL2) expression. In chromatin immunoprecipitation assays, C/EBPβ directly bound to the promoter region of IRF4, BLIMP1, and BCL2. Our data indicate that C/EBPβ is involved in the regulatory network of transcription factors that are critical for plasma cell differentiation and survival. Targeting C/EBPβ may provide a novel therapeutic strategy in the treatment of multiple myeloma. PMID:19717648

  4. Large-scale screening of transcription factor-promoter interactions in spruce reveals a transcriptional network involved in vascular development.

    Science.gov (United States)

    Duval, Isabelle; Lachance, Denis; Giguère, Isabelle; Bomal, Claude; Morency, Marie-Josée; Pelletier, Gervais; Boyle, Brian; MacKay, John J; Séguin, Armand

    2014-06-01

    This research aimed to investigate the role of diverse transcription factors (TFs) and to delineate gene regulatory networks directly in conifers at a relatively high-throughput level. The approach integrated sequence analyses, transcript profiling, and development of a conifer-specific activation assay. Transcript accumulation profiles of 102 TFs and potential target genes were clustered to identify groups of coordinately expressed genes. Several different patterns of transcript accumulation were observed by profiling in nine different organs and tissues: 27 genes were preferential to secondary xylem both in stems and roots, and other genes were preferential to phelloderm and periderm or were more ubiquitous. A robust system has been established as a screening approach to define which TFs have the ability to regulate a given promoter in planta. Trans-activation or repression effects were observed in 30% of TF-candidate gene promoter combinations. As a proof of concept, phylogenetic analysis and expression and trans-activation data were used to demonstrate that two spruce NAC-domain proteins most likely play key roles in secondary vascular growth as observed in other plant species. This study tested many TFs from diverse families in a conifer tree species, which broadens the knowledge of promoter-TF interactions in wood development and enables comparisons of gene regulatory networks found in angiosperms and gymnosperms.

  5. Integrative analysis of time course microarray data and DNA sequence data via log-linear models for identifying dynamic transcriptional regulatory networks.

    Science.gov (United States)

    Choi, Hyung-Seok; Kim, Youngchul; Cho, Kwang-Hyun; Park, Taesung

    2013-01-01

    Since eukaryotic transcription is regulated by sets of Transcription Factors (TFs) having various transcriptional time delays, identification of temporal combinations of activated TFs is important to reconstruct Transcriptional Regulatory Networks (TRNs). Our methods combine time course microarray data, information on physical binding between the TFs and their targets and the regulatory sequences of genes using a log-linear model to reconstruct dynamic functional TRNs of the yeast cell cycle and human apoptosis. In conclusion, our results suggest that the proposed dynamic motif search method is more effective in reconstructing TRNs than the static motif search method.

  6. A Gata3-Mafb transcriptional network directs post-synaptic differentiation in synapses specialized for hearing.

    Science.gov (United States)

    Yu, Wei-Ming; Appler, Jessica M; Kim, Ye-Hyun; Nishitani, Allison M; Holt, Jeffrey R; Goodrich, Lisa V

    2013-12-10

    Information flow through neural circuits is determined by the nature of the synapses linking the subtypes of neurons. How neurons acquire features distinct to each synapse remains unknown. We show that the transcription factor Mafb drives the formation of auditory ribbon synapses, which are specialized for rapid transmission from hair cells to spiral ganglion neurons (SGNs). Mafb acts in SGNs to drive differentiation of the large postsynaptic density (PSD) characteristic of the ribbon synapse. In Mafb mutant mice, SGNs fail to develop normal PSDs, leading to reduced synapse number and impaired auditory responses. Conversely, increased Mafb accelerates synaptogenesis. Moreover, Mafb is responsible for executing one branch of the SGN differentiation program orchestrated by the Gata3 transcriptional network. Remarkably, restoration of Mafb rescues the synapse defect in Gata3 mutants. Hence, Mafb is a powerful regulator of cell-type specific features of auditory synaptogenesis that offers a new entry point for treating hearing loss. DOI: http://dx.doi.org/10.7554/eLife.01341.001.

  7. Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

    Science.gov (United States)

    Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

    2011-10-04

    Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

  8. HIV transcription is induced with some forms of cell killing

    Energy Technology Data Exchange (ETDEWEB)

    Woloschak, G.E. [Argonne National Lab., IL (United States); Schreck, S. [Argonne National Lab., IL (United States)][South Carolina Univ., Columbia, SC (United States). Dept. of Chemistry; Panozzo, J. [Loyola Univ. Medical Center, Maywood, IL (United States); Chang-Liu, C.-M. [Argonne National Lab., IL (United States); Libertin, C.R. [Loyola Univ. Medical Center, Maywood, IL (United States)

    1996-11-01

    Using HeLa cells stably transfected with an HIV-LTR-CAT construct`, we demonstrated a peak in CAT induction that occurs in viable (but not necessarily cell-division-competent) cells 24 h following exposure to some cell-killing agents. {Gamma} rays were the only cell-killing agent which did not induce HIV transcription; this can be attributed to the fact that {gamma}-ray-induced apoptotic death requires function p53, which is missing in HeLa cells. For all other agents, HIV-LTR induction was dose-dependent and correlated with the amount of cell killing that occurred in the culture.

  9. Bayesian non-negative factor analysis for reconstructing transcription factor mediated regulatory networks

    Directory of Open Access Journals (Sweden)

    Chen Yidong

    2011-10-01

    Full Text Available Abstract Background Transcriptional regulation by transcription factor (TF controls the time and abundance of mRNA transcription. Due to the limitation of current proteomics technologies, large scale measurements of protein level activities of TFs is usually infeasible, making computational reconstruction of transcriptional regulatory network a difficult task. Results We proposed here a novel Bayesian non-negative factor model for TF mediated regulatory networks. Particularly, the non-negative TF activities and sample clustering effect are modeled as the factors from a Dirichlet process mixture of rectified Gaussian distributions, and the sparse regulatory coefficients are modeled as the loadings from a sparse distribution that constrains its sparsity using knowledge from database; meantime, a Gibbs sampling solution was developed to infer the underlying network structure and the unknown TF activities simultaneously. The developed approach has been applied to simulated system and breast cancer gene expression data. Result shows that, the proposed method was able to systematically uncover TF mediated transcriptional regulatory network structure, the regulatory coefficients, the TF protein level activities and the sample clustering effect. The regulation target prediction result is highly coordinated with the prior knowledge, and sample clustering result shows superior performance over previous molecular based clustering method. Conclusions The results demonstrated the validity and effectiveness of the proposed approach in reconstructing transcriptional networks mediated by TFs through simulated systems and real data.

  10. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional...... transcriptional regulatory interactions to genome-scale metabolic models in a quantitative manner....

  11. Nato3 integrates with the Shh-Foxa2 transcriptional network regulating the differentiation of midbrain dopaminergic neurons.

    Science.gov (United States)

    Nissim-Eliraz, Einat; Zisman, Sophie; Schatz, Omri; Ben-Arie, Nissim

    2013-09-01

    Mesencephalic dopaminergic (mesDA) neurons originate from the floor plate of the midbrain, a transient embryonic organizing center located at the ventral-most midline. Since the loss of mesDA leads to Parkinson's disease, the molecular mechanisms controlling the genesis and differentiation of dopaminergic progenitors are extensively studied and the identification and characterization of new genes is of interest. Here, we show that the expression of the basic helix-loop-helix transcription factor Nato3 (Ferd3l) increases in parallel to the differentiation of SN4741 dopaminergic cells in vitro. Nato3 transcription is directly regulated by the transcription factor Foxa2, a target and effector of the Sonic hedgehog (Shh) signaling cascade. Moreover, pharmacological inhibition of Shh signaling downregulated the expression of Nato3, thus defining Nato3 as a novel component of one of the major pathways controlling cell patterning and generation of mesDA. Furthermore, we show that Nato3 regulated Shh and Foxa2 through a novel feed-backward loop. Up- and downregulation of Nato3 further affected the transcription of Nurr1, implicated in the genesis of mesDA, but not of TH. Taken together, these data shed new light on the transcriptional networks controlling the generation of mesDA and may be utilized in the efforts to direct stem cells towards a dopaminergic fate.

  12. Analysis of protein interaction networks related to core transcription factors target genes in embryonic stem cells%胚胎干细胞核心转录因子靶基因集蛋白互作网络特征分析

    Institute of Scientific and Technical Information of China (English)

    左长清; 汪宗桂; 吴铁; 崔燎

    2011-01-01

    BACKGROUND: It is sufficient to reprogram somatic cells, through transduction of some core transcription factors, into pluripotent stem cells (iPS) that exhibit the essential characteristics of embryonic stem (ES) cells. At present, the complex mechanism is not yet fully understood.OBJECTIVE: To study the protein interaction networks related to core transcription factors target genes in embryonic stem cells and to obtain regulatory mechanism controlled "stemness".METHODS: Non-redundant protein interaction data (NRPD) were obtained after removal of redundant data in BioGRID database.Protein interaction pairs, formed by the target genes, were extracted by perl program and the largest continuous protein interaction networks were obtained through searching NRPD using breadth-first search algorithm. At the same time, 1 000 random networks were analyzed and compared. At last, network visualization was analyzed through the Cytoscape software and network characteristics were explained using complex scale-free network model of Barabasi-Albert.RESULTS AND CONCLUSION : More protein interaction pairs and larger continuous protein network, statistically significant difference compared with random genes, were formed by core transcription factor target genes. The continuous protein network is scale-free characteristics of complex networks. This study has suggested that target genes may regulate synergistically "stemness" characteristics of embryonic stem cells through close interaction and forming a network module.%背景:外源性核心转录因子导入终末分化细胞能产生具有与胚胎干细胞特性相似的诱导多潜能干细胞,其复杂机制目前尚未完全阐明.目的:分析核心转录因子靶基因集蛋白互作网络特征,获得其影响"干性"特征的调控机制.方法:去除BioGRID数据库中的冗余数据,获得非冗余蛋白互作数据库.perl程序搜索靶基因集组成的蛋白互作对,广度优先算法搜索非冗余蛋白互作数

  13. Systematic repression of transcription factors reveals limited patterns of gene expression changes in ES cells

    Science.gov (United States)

    Nishiyama, Akira; Sharov, Alexei A.; Piao, Yulan; Amano, Misa; Amano, Tomokazu; Hoang, Hien G.; Binder, Bernard Y.; Tapnio, Richard; Bassey, Uwem; Malinou, Justin N.; Correa-Cerro, Lina S.; Yu, Hong; Xin, Li; Meyers, Emily; Zalzman, Michal; Nakatake, Yuhki; Stagg, Carole; Sharova, Lioudmila; Qian, Yong; Dudekula, Dawood; Sheer, Sarah; Cadet, Jean S.; Hirata, Tetsuya; Yang, Hsih-Te; Goldberg, Ilya; Evans, Michele K.; Longo, Dan L.; Schlessinger, David; Ko, Minoru S. H.

    2013-01-01

    Networks of transcription factors (TFs) are thought to determine and maintain the identity of cells. Here we systematically repressed each of 100 TFs with shRNA and carried out global gene expression profiling in mouse embryonic stem (ES) cells. Unexpectedly, only the repression of a handful of TFs significantly affected transcriptomes, which changed in two directions/trajectories: one trajectory by the repression of either Pou5f1 or Sox2; the other trajectory by the repression of either Esrrb, Sall4, Nanog, or Tcfap4. The data suggest that the trajectories of gene expression change are already preconfigured by the gene regulatory network and roughly correspond to extraembryonic and embryonic fates of cell differentiation, respectively. These data also indicate the robustness of the pluripotency gene network, as the transient repression of most TFs did not alter the transcriptomes. PMID:23462645

  14. FOXA and master transcription factors recruit Mediator and Cohesin to the core transcriptional regulatory circuitry of cancer cells

    Science.gov (United States)

    Fournier, Michèle; Bourriquen, Gaëlle; Lamaze, Fabien C.; Côté, Maxime C.; Fournier, Éric; Joly-Beauparlant, Charles; Caron, Vicky; Gobeil, Stéphane; Droit, Arnaud; Bilodeau, Steve

    2016-10-01

    Controlling the transcriptional program is essential to maintain the identity and the biological functions of a cell. The Mediator and Cohesin complexes have been established as central cofactors controlling the transcriptional program in normal cells. However, the distribution, recruitment and importance of these complexes in cancer cells have not been fully investigated. Here we show that FOXA and master transcription factors are part of the core transcriptional regulatory circuitry of cancer cells and are essential to recruit M ediator and Cohesin. Indeed, Mediator and Cohesin occupied the enhancer and promoter regions of actively transcribed genes and maintained the proliferation and colony forming potential. Through integration of publically available ChIP-Seq datasets, we predicted the core transcriptional regulatory circuitry of each cancer cell. Unexpectedly, for all cells investigated, the pioneer transcription factors FOXA1 and/or FOXA2 were identified in addition to cell-specific master transcription factors. Loss of both types of transcription factors phenocopied the loss of Mediator and Cohesin. Lastly, the master and pioneer transcription factors were essential to recruit Mediator and Cohesin to regulatory regions of actively transcribed genes. Our study proposes that maintenance of the cancer cell state is dependent on recruitment of Mediator and Cohesin through FOXA and master transcription factors.

  15. FOXA and master transcription factors recruit Mediator and Cohesin to the core transcriptional regulatory circuitry of cancer cells.

    Science.gov (United States)

    Fournier, Michèle; Bourriquen, Gaëlle; Lamaze, Fabien C; Côté, Maxime C; Fournier, Éric; Joly-Beauparlant, Charles; Caron, Vicky; Gobeil, Stéphane; Droit, Arnaud; Bilodeau, Steve

    2016-10-14

    Controlling the transcriptional program is essential to maintain the identity and the biological functions of a cell. The Mediator and Cohesin complexes have been established as central cofactors controlling the transcriptional program in normal cells. However, the distribution, recruitment and importance of these complexes in cancer cells have not been fully investigated. Here we show that FOXA and master transcription factors are part of the core transcriptional regulatory circuitry of cancer cells and are essential to recruit M ediator and Cohesin. Indeed, Mediator and Cohesin occupied the enhancer and promoter regions of actively transcribed genes and maintained the proliferation and colony forming potential. Through integration of publically available ChIP-Seq datasets, we predicted the core transcriptional regulatory circuitry of each cancer cell. Unexpectedly, for all cells investigated, the pioneer transcription factors FOXA1 and/or FOXA2 were identified in addition to cell-specific master transcription factors. Loss of both types of transcription factors phenocopied the loss of Mediator and Cohesin. Lastly, the master and pioneer transcription factors were essential to recruit Mediator and Cohesin to regulatory regions of actively transcribed genes. Our study proposes that maintenance of the cancer cell state is dependent on recruitment of Mediator and Cohesin through FOXA and master transcription factors.

  16. FOXA and master transcription factors recruit Mediator and Cohesin to the core transcriptional regulatory circuitry of cancer cells

    Science.gov (United States)

    Fournier, Michèle; Bourriquen, Gaëlle; Lamaze, Fabien C.; Côté, Maxime C.; Fournier, Éric; Joly-Beauparlant, Charles; Caron, Vicky; Gobeil, Stéphane; Droit, Arnaud; Bilodeau, Steve

    2016-01-01

    Controlling the transcriptional program is essential to maintain the identity and the biological functions of a cell. The Mediator and Cohesin complexes have been established as central cofactors controlling the transcriptional program in normal cells. However, the distribution, recruitment and importance of these complexes in cancer cells have not been fully investigated. Here we show that FOXA and master transcription factors are part of the core transcriptional regulatory circuitry of cancer cells and are essential to recruit M ediator and Cohesin. Indeed, Mediator and Cohesin occupied the enhancer and promoter regions of actively transcribed genes and maintained the proliferation and colony forming potential. Through integration of publically available ChIP-Seq datasets, we predicted the core transcriptional regulatory circuitry of each cancer cell. Unexpectedly, for all cells investigated, the pioneer transcription factors FOXA1 and/or FOXA2 were identified in addition to cell-specific master transcription factors. Loss of both types of transcription factors phenocopied the loss of Mediator and Cohesin. Lastly, the master and pioneer transcription factors were essential to recruit Mediator and Cohesin to regulatory regions of actively transcribed genes. Our study proposes that maintenance of the cancer cell state is dependent on recruitment of Mediator and Cohesin through FOXA and master transcription factors. PMID:27739523

  17. Transcriptional networks in the nitrate response of Arabidopsis thaliana.

    Science.gov (United States)

    Vidal, Elena A; Álvarez, José M; Moyano, Tomás C; Gutiérrez, Rodrigo A

    2015-10-01

    Nitrogen is an essential macronutrient for plants and its availability is a key determinant of plant growth and development and crop yield. Besides their nutritional role, N nutrients and metabolites are signals that activate signaling pathways that modulate many plant processes. Because the most abundant inorganic N source for plants in agronomic soils is nitrate, much of the work to understand plant N-signaling has focused on this nutrient. Over the last years, several studies defined a comprehensive catalog of nitrate-responsive genes, involved in nitrate transport, metabolism and a variety of other processes. Despite significant progress in recent years, primarily using Arabidopsis thaliana as a model system, the molecular mechanisms by which nitrate elicits changes in transcript abundance are still not fully understood. Here we highlight recent advancements in identifying key transcription factors and transcriptional mechanisms that orchestrate the gene expression response to changes in nitrate availability in A. thaliana.

  18. Diversification in the genetic architecture of gene expression and transcriptional networks in organ differentiation of Populus

    OpenAIRE

    Drost, Derek R.; Benedict, Catherine I.; Berg, Arthur; Novaes, Evandro; Novaes, Carolina R. D. B.; Yu, Qibin; Dervinis, Christopher; Jessica M Maia; Yap, John; Miles, Brianna; Kirst, Matias

    2010-01-01

    A fundamental goal of systems biology is to identify genetic elements that contribute to complex phenotypes and to understand how they interact in networks predictive of system response to genetic variation. Few studies in plants have developed such networks, and none have examined their conservation among functionally specialized organs. Here we used genetical genomics in an interspecific hybrid population of the model hardwood plant Populus to uncover transcriptional networks in xylem, leav...

  19. Plant stem cell maintenance involves direct transcriptional repression of differentiation program.

    Science.gov (United States)

    Yadav, Ram Kishor; Perales, Mariano; Gruel, Jérémy; Ohno, Carolyn; Heisler, Marcus; Girke, Thomas; Jönsson, Henrik; Reddy, G Venugopala

    2013-01-01

    In animal systems, master regulatory transcription factors (TFs) mediate stem cell maintenance through a direct transcriptional repression of differentiation promoting TFs. Whether similar mechanisms operate in plants is not known. In plants, shoot apical meristems serve as reservoirs of stem cells that provide cells for all above ground organs. WUSCHEL, a homeodomain TF produced in cells of the niche, migrates into adjacent cells where it specifies stem cells. Through high-resolution genomic analysis, we show that WUSCHEL represses a large number of genes that are expressed in differentiating cells including a group of differentiation promoting TFs involved in leaf development. We show that WUS directly binds to the regulatory regions of differentiation promoting TFs; KANADI1, KANADI2, ASYMMETRICLEAVES2 and YABBY3 to repress their expression. Predictions from a computational model, supported by live imaging, reveal that WUS-mediated repression prevents premature differentiation of stem cell progenitors, being part of a minimal regulatory network for meristem maintenance. Our work shows that direct transcriptional repression of differentiation promoting TFs is an evolutionarily conserved logic for stem cell regulation.

  20. THE EN1 TRANSCRIPTIONAL NETWORK IN MESODIENCEPHALIC DOPAMINERGIC NEURONS

    NARCIS (Netherlands)

    Alves dos Santos, M.T.M.

    2011-01-01

    The transcription factor engrailed 1 (En1) is essential in mdDA neuron maintenance, both during embryonic development and adulthood. The overall aims of this thesis were to unravel the function of En1, at a molecular level, in mdDA neuron development and to determine its relationship to canonical Wn

  1. Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems.

    Science.gov (United States)

    Takahashi, Melissa K; Chappell, James; Hayes, Clarmyra A; Sun, Zachary Z; Kim, Jongmin; Singhal, Vipul; Spring, Kevin J; Al-Khabouri, Shaima; Fall, Christopher P; Noireaux, Vincent; Murray, Richard M; Lucks, Julius B

    2015-05-15

    RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

  2. Checkpoint Kinases Regulate a Global Network of Transcription Factors in Response to DNA Damage

    Directory of Open Access Journals (Sweden)

    Eric J. Jaehnig

    2013-07-01

    Full Text Available DNA damage activates checkpoint kinases that induce several downstream events, including widespread changes in transcription. However, the specific connections between the checkpoint kinases and downstream transcription factors (TFs are not well understood. Here, we integrate kinase mutant expression profiles, transcriptional regulatory interactions, and phosphoproteomics to map kinases and downstream TFs to transcriptional regulatory networks. Specifically, we investigate the role of the Saccharomyces cerevisiae checkpoint kinases (Mec1, Tel1, Chk1, Rad53, and Dun1 in the transcriptional response to DNA damage caused by methyl methanesulfonate. The result is a global kinase-TF regulatory network in which Mec1 and Tel1 signal through Rad53 to synergistically regulate the expression of more than 600 genes. This network involves at least nine TFs, many of which have Rad53-dependent phosphorylation sites, as regulators of checkpoint-kinase-dependent genes. We also identify a major DNA damage-induced transcriptional network that regulates stress response genes independently of the checkpoint kinases.

  3. Preparation of cell lines for single-cell analysis of transcriptional activation dynamics.

    Science.gov (United States)

    Rafalska-Metcalf, Ilona U; Janicki, Susan M

    2013-01-01

    Imaging molecularly defined regions of chromatin in single living cells during transcriptional activation has the potential to provide new insight into gene regulatory mechanisms. Here, we describe a method for isolating cell lines with multi-copy arrays of reporter transgenes, which can be used for real-time high-resolution imaging of transcriptional activation dynamics in single cells.

  4. A dynamic network of transcription in LPS-treated human subjects

    Directory of Open Access Journals (Sweden)

    Moldawer Lyle L

    2009-07-01

    Full Text Available Abstract Background Understanding the transcriptional regulatory networks that map out the coordinated dynamic responses of signaling proteins, transcription factors and target genes over time would represent a significant advance in the application of genome wide expression analysis. The primary challenge is monitoring transcription factor activities over time, which is not yet available at the large scale. Instead, there have been several developments to estimate activities computationally. For example, Network Component Analysis (NCA is an approach that can predict transcription factor activities over time as well as the relative regulatory influence of factors on each target gene. Results In this study, we analyzed a gene expression data set in blood leukocytes from human subjects administered with lipopolysaccharide (LPS, a prototypical inflammatory challenge, in the context of a reconstructed regulatory network including 10 transcription factors, 99 target genes and 149 regulatory interactions. We found that the computationally estimated activities were well correlated to their coordinated action. Furthermore, we found that clustering the genes in the context of regulatory influences greatly facilitated interpretation of the expression data, as clusters of gene expression corresponded to the activity of specific factors or more interestingly, factor combinations which suggest coordinated regulation of gene expression. The resulting clusters were therefore more biologically meaningful, and also led to identification of additional genes under the same regulation. Conclusion Using NCA, we were able to build a network that accounted for between 8–11% genes in the known transcriptional response to LPS in humans. The dynamic network illustrated changes of transcription factor activities and gene expressions as well as interactions of signaling proteins, transcription factors and target genes.

  5. Alternative Polyadenylation Regulates CELF1/CUGBP1 Target Transcripts Following T Cell Activation

    Science.gov (United States)

    Beisang, Daniel; Reilly, Cavan; Bohjanen, Paul R.

    2014-01-01

    Alternative polyadenylation (APA) is an evolutionarily conserved mechanism for regulating gene expression. Transcript 3′ end shortening through changes in polyadenylation site usage occurs following T cell activation, but the consequences of APA on gene expression are poorly understood. We previously showed that GU-rich elements (GREs) found in the 3′ untranslated regions of select transcripts mediate rapid mRNA decay by recruiting the protein CELF1/CUGBP1. Using a global RNA sequencing approach, we found that a network of CELF1 target transcripts involved in cell division underwent preferential 3′ end shortening via APA following T cell activation, resulting in decreased inclusion of CELF1 binding sites and increased transcript expression. We present a model whereby CELF1 regulates APA site selection following T cell activation through reversible binding to nearby GRE sequences. These findings provide insight into the role of APA in controlling cellular proliferation during biological processes such as development, oncogenesis and T cell activation PMID:25123787

  6. A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

    Directory of Open Access Journals (Sweden)

    Chandra Nagasuma R

    2009-02-01

    Full Text Available Abstract Background A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN from transcript profiling data. Results The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting problem and solved finally by formulating a Linear Program (LP. A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known

  7. C. elegans BED domain transcription factor BED-3 controls lineage-specific cell proliferation during organogenesis.

    Science.gov (United States)

    Inoue, Takao; Sternberg, Paul W

    2010-02-15

    The control of cell division is critical to organogenesis, but how this control is achieved is not fully understood. We found that mutations in bed-3, encoding a BED Zn-finger domain transcription factor, confer a phenotype where a specific set of cell divisions during vulval organogenesis is lost. Unlike general cell cycle regulators in Caenorhabditis elegans, the function of bed-3 is restricted to specific lineages. Transcriptional reporters suggest that bed-3 is expressed in a limited number of cell types including vulval cells whose divisions are affected in bed-3 mutants. A bed-3 mutation also affects the expression pattern of the cdh-3 cadherin gene in the vulva. The phenotype of bed-3 mutants is similar to the phenotype caused by mutations in cog-1 (Nkx6), a component of a gene regulatory network controlling cell type specific gene expression in the vulval lineage. These results suggest that bed-3 is a key component linking the gene regulatory network controlling cell-type specification to control of cell division during vulval organogenesis.

  8. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Science.gov (United States)

    Sayyed-Ahmad, Abdallah; Tuncay, Kagan; Ortoleva, Peter J

    2007-01-01

    Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs) is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF) thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the construction of the network of

  9. Transcriptional regulatory network refinement and quantification through kinetic modeling, gene expression microarray data and information theory

    Directory of Open Access Journals (Sweden)

    Tuncay Kagan

    2007-01-01

    Full Text Available Abstract Background Gene expression microarray and other multiplex data hold promise for addressing the challenges of cellular complexity, refined diagnoses and the discovery of well-targeted treatments. A new approach to the construction and quantification of transcriptional regulatory networks (TRNs is presented that integrates gene expression microarray data and cell modeling through information theory. Given a partial TRN and time series data, a probability density is constructed that is a functional of the time course of transcription factor (TF thermodynamic activities at the site of gene control, and is a function of mRNA degradation and transcription rate coefficients, and equilibrium constants for TF/gene binding. Results Our approach yields more physicochemical information that compliments the results of network structure delineation methods, and thereby can serve as an element of a comprehensive TRN discovery/quantification system. The most probable TF time courses and values of the aforementioned parameters are obtained by maximizing the probability obtained through entropy maximization. Observed time delays between mRNA expression and activity are accounted for implicitly since the time course of the activity of a TF is coupled by probability functional maximization, and is not assumed to be proportional to expression level of the mRNA type that translates into the TF. This allows one to investigate post-translational and TF activation mechanisms of gene regulation. Accuracy and robustness of the method are evaluated. A kinetic formulation is used to facilitate the analysis of phenomena with a strongly dynamical character while a physically-motivated regularization of the TF time course is found to overcome difficulties due to omnipresent noise and data sparsity that plague other methods of gene expression data analysis. An application to Escherichia coli is presented. Conclusion Multiplex time series data can be used for the

  10. OpaR controls a network of downstream transcription factors in Vibrio parahaemolyticus BB22OP.

    Directory of Open Access Journals (Sweden)

    Alison Kernell Burke

    Full Text Available Vibrio parahaemolyticus is an emerging world-wide human pathogen that is associated with food-borne gastroenteritis when raw or undercooked seafood is consumed. Expression of virulence factors in this organism is modulated by the phenomenon known as quorum sensing, which permits differential gene regulation at low versus high cell density. The master regulator of quorum sensing in V. parahaemolyticus is OpaR. OpaR not only controls virulence factor gene expression, but also the colony and cellular morphology associated with growth on a surface and biofilm formation. Whole transcriptome Next Generation sequencing (RNA-Seq was utilized to determine the OpaR regulon by comparing strains BB22OP (opaR+, LM5312 and BB22TR (∆opaR1, LM5674. This work, using the published V. parahaemolyticus BB22OP genome sequence, confirms and expands upon a previous microarray analysis for these two strains that used an Affymetrix GeneChip designed from the closely related V. parahaemolyticus RIMD2210633 genome sequence. Overall there was excellent correlation between the microarray and RNA-Seq data. Eleven transcription factors under OpaR control were identified by both methods and further confirmed by quantitative reverse transcription PCR (qRT-PCR analysis. Nine of these transcription factors were demonstrated to be direct OpaR targets via in vitro electrophoretic mobility shift assays with purified hexahistidine-tagged OpaR. Identification of the direct and indirect targets of OpaR, including small RNAs, will enable the construction of a network map of regulatory interactions important for the switch between the nonpathogenic and pathogenic states.

  11. Integrated pathway-based transcription regulation network mining and visualization based on gene expression profiles.

    Science.gov (United States)

    Kibinge, Nelson; Ono, Naoaki; Horie, Masafumi; Sato, Tetsuo; Sugiura, Tadao; Altaf-Ul-Amin, Md; Saito, Akira; Kanaya, Shigehiko

    2016-06-01

    Conventionally, workflows examining transcription regulation networks from gene expression data involve distinct analytical steps. There is a need for pipelines that unify data mining and inference deduction into a singular framework to enhance interpretation and hypotheses generation. We propose a workflow that merges network construction with gene expression data mining focusing on regulation processes in the context of transcription factor driven gene regulation. The pipeline implements pathway-based modularization of expression profiles into functional units to improve biological interpretation. The integrated workflow was implemented as a web application software (TransReguloNet) with functions that enable pathway visualization and comparison of transcription factor activity between sample conditions defined in the experimental design. The pipeline merges differential expression, network construction, pathway-based abstraction, clustering and visualization. The framework was applied in analysis of actual expression datasets related to lung, breast and prostrate cancer. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Mapping Transcriptional Networks in Plants: Data-Driven Discovery of Novel Biological Mechanisms.

    Science.gov (United States)

    Gaudinier, Allison; Brady, Siobhan M

    2016-04-29

    In plants, systems biology approaches have led to the generation of a variety of large data sets. Many of these data are created to elucidate gene expression profiles and their corresponding transcriptional regulatory mechanisms across a range of tissue types, organs, and environmental conditions. In an effort to map the complexity of this transcriptional regulatory control, several types of experimental assays have been used to map transcriptional regulatory networks. In this review, we discuss how these methods can be best used to identify novel biological mechanisms by focusing on the appropriate biological context. Translating network biology back to gene function in the plant, however, remains a challenge. We emphasize the need for validation and insight into the underlying biological processes to successfully exploit systems approaches in an effort to determine the emergent properties revealed by network analyses.

  13. ATF-2 regulates lipopolysaccharide-induced transcription in macrophage cells.

    Science.gov (United States)

    Hirose, Noriyuki; Maekawa, Toshio; Shinagawa, Toshie; Ishii, Shunsuke

    2009-07-17

    The transcription factor ATF-2, a member of the ATF/CREB family, is a target of p38 that are involved in stress-induced apoptosis and in Toll-like receptor (TLR)-mediated signaling. Phosphorylation of ATF-2 at Thr-71 was enhanced by treating of RAW264.7 macrophage cells with either LPS, MALP-2, or CpG-ODN. LPS treatment enhanced the trans-activation capacity of ATF-2. Among multiple LPS-induced genes, the LPS-induced expression of Socs-3 was significantly reduced by the treatment of RAW264.7 cells with an Atf-2 siRNA. Transcription from the Socs-3 promoter was synergistically stimulated by ATF-2 and LPS, whereas it was suppressed by Atf-2 siRNA. Histone deacetylase 1 (HDAC1) interacted with ATF-2 after LPS treatment, but not before treatment. Treatment of RAW264.7 cells with trichostatin A, an inhibitor of HDAC, suppressed the LPS-induced Socs-3 expression, suggesting that HDAC1 positively regulates the LPS-induced transcription of Socs-3. Thus, ATF-2 plays an important role in TLR-mediated transcriptional control in macrophage cells.

  14. Transcriptional interference networks coordinate the expression of functionally-related genes clustered in the same genomic loci

    Directory of Open Access Journals (Sweden)

    Zsolt eBoldogkoi

    2012-07-01

    Full Text Available The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organisation, transcription, various post-transcriptional processes and translation. In this study, the Transcriptional Interference Network (TIN hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighbouring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally-linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly-arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely-oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronised cascade of gene expression in functionally-linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular

  15. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Directory of Open Access Journals (Sweden)

    Kovaleva Galina

    2011-06-01

    Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

  16. Origin of cells and network information

    Institute of Scientific and Technical Information of China (English)

    Shihori Tanabe

    2015-01-01

    All cells are derived from one cell, and the origin ofdifferent cell types is a subject of curiosity. Cells constructlife through appropriately timed networks at each stageof development. Communication among cells andintracellular signaling are essential for cell differentiationand for life processes. Cellular molecular networksestablish cell diversity and life. The investigation ofthe regulation of each gene in the genome within thecellular network is therefore of interest. Stem cellsproduce various cells that are suitable for specificpurposes. The dynamics of the information in thecellular network changes as the status of cells isaltered. The components of each cell are subject toinvestigation.

  17. Roles of signaling and transcriptional networks in pathological lymphangiogenesis.

    Science.gov (United States)

    Yoshimatsu, Yasuhiro; Miyazaki, Hideki; Watabe, Tetsuro

    2016-04-01

    Lymphangiogenesis, the generation of new lymphatic vessels, plays important roles in cancer metastasis. Outstanding progress during the past decade has dramatically increased the novel knowledge and insights of the mechanisms underlying the generation of new lymphatic vessels, the roles of transcription factors and lymphangiogenic growth factors during physiological development and pathological processes such as cancer and inflammation. Furthermore, an understanding of the molecular consequences during tumor lymphangiogenesis has provided chances to develop better diagnostic and therapeutic approaches that aim to limit the progression of cancer. In this article, we will explain the current knowledge of how lymphatic function is altered in various pathological conditions including cancer progression.

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

    Directory of Open Access Journals (Sweden)

    Delyon Bernard

    2010-11-01

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

  19. Quantitative levels of Deficiens and Globosa during late petal development show a complex transcriptional network topology of B function.

    Science.gov (United States)

    Manchado-Rojo, María; Delgado-Benarroch, Luciana; Roca, María J; Weiss, Julia; Egea-Cortines, Marcos

    2012-10-01

    The transcriptional network topology of B function in Antirrhinum, required for petal and stamen development, is thought to rely on initial activation of transcription of DEFICIENS (DEF) and GLOBOSA (GLO), followed by a positive autoregulatory loop maintaining gene expression levels. Here, we show that the mutant compacta (co), whose vegetative growth and petal size are affected, plays a role in B function. Late events in petal morphogenesis such as development of conical cell area and scent emissions were reduced in co and def (nicotianoides) (def (nic) ), and absent in co def (nic) double mutants, suggesting a role for CO in petal identity. Expression of DEF was down-regulated in co but surprisingly GLO was not affected. We investigated the levels of DEF and GLO at late stages of petal development in the co, def (nic) and glo-1 mutants, and established a reliable transformation protocol that yielded RNAi-DEF lines. We show that the threshold levels of DEF or GLO required to obtain petal tissue are approximately 11% of wild-type. The relationship between DEF and GLO transcripts is not equal or constant and changes during development. Furthermore, down-regulation of DEF or GLO does not cause parallel down-regulation of the partner. Our results demonstrate that, at late stages of petal development, the B function transcriptional network topology is not based on positive autoregulation, and has additional components of transcriptional maintenance. Our results suggest changes in network topology that may allow changes in protein complexes that would explain the fact that not all petal traits appear early in development.

  20. An interaction network of mental disorder proteins in neural stem cells.

    Science.gov (United States)

    Moen, M J; Adams, H H H; Brandsma, J H; Dekkers, D H W; Akinci, U; Karkampouna, S; Quevedo, M; Kockx, C E M; Ozgür, Z; van IJcken, W F J; Demmers, J; Poot, R A

    2017-04-04

    Mental disorders (MDs) such as intellectual disability (ID), autism spectrum disorders (ASD) and schizophrenia have a strong genetic component. Recently, many gene mutations associated with ID, ASD or schizophrenia have been identified by high-throughput sequencing. A substantial fraction of these mutations are in genes encoding transcriptional regulators. Transcriptional regulators associated with different MDs but acting in the same gene regulatory network provide information on the molecular relation between MDs. Physical interaction between transcriptional regulators is a strong predictor for their cooperation in gene regulation. Here, we biochemically purified transcriptional regulators from neural stem cells, identified their interaction partners by mass spectrometry and assembled a protein interaction network containing 206 proteins, including 68 proteins mutated in MD patients and 52 proteins significantly lacking coding variation in humans. Our network shows molecular connections between established MD proteins and provides a discovery tool for novel MD genes. Network proteins preferentially co-localize on the genome and cooperate in disease-relevant gene regulation. Our results suggest that the observed transcriptional regulators associated with ID, ASD or schizophrenia are part of a transcriptional network in neural stem cells. We find that more severe mutations in network proteins are associated with MDs that include lower intelligence quotient (IQ), suggesting that the level of disruption of a shared transcriptional network correlates with cognitive dysfunction.

  1. Long noncoding RNAs as a novel component of the Myc transcriptional network

    NARCIS (Netherlands)

    Winkle, Melanie; van den Berg, Anke; Tayari, Masoumeh; Sietzema, Jantine; Terpstra, Martijn; Kortman, Gertrud; de Jong, Debora; Visser, Lydia; Diepstra, Arjan; Kok, Klaas; Kluiver, Joost

    2015-01-01

    Myc is a well-known transcription factor with important roles in cell cycle, apoptosis, and cellular transformation. Long noncoding RNAs (lncRNAs) have recently emerged as an important class of regulatory RNAs. Here, we show that lncRNAs are a main component of the Myc-regulated transcriptional prog

  2. Gene array analysis of neural crest cells identifies transcription factors necessary for direct conversion of embryonic fibroblasts into neural crest cells

    Directory of Open Access Journals (Sweden)

    Tsutomu Motohashi

    2016-03-01

    Full Text Available Neural crest cells (NC cells are multipotent cells that emerge from the edge of the neural folds and migrate throughout the developing embryo. Although the gene regulatory network for generation of NC cells has been elucidated in detail, it has not been revealed which of the factors in the network are pivotal to directing NC identity. In this study we analyzed the gene expression profile of a pure NC subpopulation isolated from Sox10-IRES-Venus mice and investigated whether these genes played a key role in the direct conversion of Sox10-IRES-Venus mouse embryonic fibroblasts (MEFs into NC cells. The comparative molecular profiles of NC cells and neural tube cells in 9.5-day embryos revealed genes including transcription factors selectively expressed in developing trunk NC cells. Among 25 NC cell-specific transcription factor genes tested, SOX10 and SOX9 were capable of converting MEFs into SOX10-positive (SOX10+ cells. The SOX10+ cells were then shown to differentiate into neurons, glial cells, smooth muscle cells, adipocytes and osteoblasts. These SOX10+ cells also showed limited self-renewal ability, suggesting that SOX10 and SOX9 directly converted MEFs into NC cells. Conversely, the remaining transcription factors, including well-known NC cell specifiers, were unable to convert MEFs into SOX10+ NC cells. These results suggest that SOX10 and SOX9 are the key factors necessary for the direct conversion of MEFs into NC cells.

  3. Helicase-like transcription factor (Hltf regulates G2/M transition, Wt1/Gata4/Hif-1a cardiac transcription networks, and collagen biogenesis.

    Directory of Open Access Journals (Sweden)

    Rebecca A Helmer

    Full Text Available HLTF/Hltf regulates transcription, remodels chromatin, and coordinates DNA damage repair. Hltf is expressed in mouse brain and heart during embryonic and postnatal development. Silencing Hltf is semilethal. Seventy-four percent of congenic C57BL/6J Hltf knockout mice died, 75% within 12-24 hours of birth. Previous studies in neonatal (6-8 hour postpartum brain revealed silencing Hltf disrupted cell cycle progression, and attenuated DNA damage repair. An RNA-Seq snapshot of neonatal heart transcriptome showed 1,536 of 20,000 total transcripts were altered (p < 0.05 - 10 up- and 1,526 downregulated. Pathway enrichment analysis with MetaCore™ showed Hltf's regulation of the G2/M transition (p=9.726E(-15 of the cell cycle in heart is nearly identical to its role in brain. In addition, Brca1 and 12 members of the Brca1 associated genome surveillance complex are also downregulated. Activation of caspase 3 coincides with transcriptional repression of Bcl-2. Hltf loss caused downregulation of Wt1/Gata4/Hif-1a signaling cascades as well as Myh7b/miR499 transcription. Hltf-specific binding to promoters and/or regulatory regions of these genes was authenticated by ChIP-PCR. Hif-1a targets for prolyl (P4ha1, P4ha2 and lysyl (Plod2 collagen hydroxylation, PPIase enzymes (Ppid, Ppif, Ppil3 for collagen trimerization, and lysyl oxidase (Loxl2 for collagen-elastin crosslinking were downregulated. However, transcription of genes for collagens, fibronectin, Mmps and their inhibitors (Timps was unaffected. The collective downregulation of genes whose protein products control collagen biogenesis caused disorganization of the interstitial and perivascular myocardial collagen fibrillar network as viewed with picrosirius red-staining, and authenticated with spectral imaging. Wavy collagen bundles in control hearts contrasted with collagen fibers that were thin, short and disorganized in Hltf null hearts. Collagen bundles in Hltf null hearts were tangled and

  4. Signaling and Transcriptional Networks in Heart Development and Regeneration

    OpenAIRE

    2013-01-01

    The mammalian heart is the first functional organ, the first indicator of life. Its normal formation and function are essential for fetal life. Defects in heart formation lead to congenital heart defects, underscoring the finesse with which the heart is assembled. Understanding the reg-ulatory networks controlling heart development have led to significant insights into its lineage origins and morphogenesis and illuminated important aspects of mammalian embryology, while providing insights int...

  5. Interrogating a cell signalling network sensitively monitors cell fate transition during early differentiation of mouse embryonic stem cells

    Institute of Scientific and Technical Information of China (English)

    LIU; Yi-Hsin; HO; Chih-ming

    2010-01-01

    The different cell types in an animal are often considered to be specified by combinations of transcription factors,and defined by marker gene expression.This paradigm is challenged,however,in stem cell research and application.Using a mouse embryonic stem cell(mESC) culture system,here we show that the expression level of many key stem cell marker genes/transcription factors such as Oct4,Sox2 and Nanog failed to monitor cell status transition during mESC differentiation.On the other hand,the response patterns of cell signalling network to external stimuli,as monitored by the dynamics of protein phosphorylation,changed dramatically.Our results also suggest that an irreversible alternation in the cell signalling network precedes the adjustment of transcription factor levels.This is consistent with the notion that signal transduction events regulate cell fate specification.We propose that interrogating a cell signalling network can assess the cell property more precisely,and provide a sensitive measurement for the early events in cell fate transition.We wish to bring attention to the potential problem of cell identification using a few marker genes,and suggest a novel methodology to address this issue.

  6. Cycling Transcriptional Networks Optimize Energy Utilization on a Genome Scale.

    Science.gov (United States)

    Wang, Guang-Zhong; Hickey, Stephanie L; Shi, Lei; Huang, Hung-Chung; Nakashe, Prachi; Koike, Nobuya; Tu, Benjamin P; Takahashi, Joseph S; Konopka, Genevieve

    2015-12-01

    Genes expressing circadian RNA rhythms are enriched for metabolic pathways, but the adaptive significance of cyclic gene expression remains unclear. We estimated the genome-wide synthetic and degradative cost of transcription and translation in three organisms and found that the cost of cycling genes is strikingly higher compared to non-cycling genes. Cycling genes are expressed at high levels and constitute the most costly proteins to synthesize in the genome. We demonstrate that metabolic cycling is accelerated in yeast grown under higher nutrient flux and the number of cycling genes increases ∼40%, which are achieved by increasing the amplitude and not the mean level of gene expression. These results suggest that rhythmic gene expression optimizes the metabolic cost of global gene expression and that highly expressed genes have been selected to be downregulated in a cyclic manner for energy conservation.

  7. A core transcriptional network for early mesoderm development in Drosophila melanogaster

    OpenAIRE

    Sandmann, Thomas; Girardot, Charles; Brehme, Marc; Tongprasit, Waraporn; Stolc, Viktor; Furlong, Eileen E.M.

    2007-01-01

    Embryogenesis is controlled by large gene-regulatory networks, which generate spatially and temporally refined patterns of gene expression. Here, we report the characteristics of the regulatory network orchestrating early mesodermal development in the fruitfly Drosophila, where the transcription factor Twist is both necessary and sufficient to drive development. Through the integration of chromatin immunoprecipitation followed by microarray analysis (ChIP-on-chip) experiments during discrete ...

  8. The transcriptional coactivator Cbp regulates self-renewal and differentiation in adult hematopoietic stem cells.

    Science.gov (United States)

    Chan, Wai-In; Hannah, Rebecca L; Dawson, Mark A; Pridans, Clare; Foster, Donna; Joshi, Anagha; Göttgens, Berthold; Van Deursen, Jan M; Huntly, Brian J P

    2011-12-01

    The transcriptional coactivator Cbp plays an important role in a wide range of cellular processes, including proliferation, differentiation, and apoptosis. Although studies have shown its requirement for hematopoietic stem cell (HSC) development, its role in adult HSC maintenance, as well as the cellular and molecular mechanisms underlying Cbp function, is not clear. Here, we demonstrate a gradual loss of phenotypic HSCs and differentiation defects following conditional ablation of Cbp during adult homeostasis. In addition, Cbp-deficient HSCs reconstituted hematopoiesis with lower efficiency than their wild-type counterparts, and this response was readily exhausted under replicative stress. This phenotype relates to an alteration in cellular fate decisions for HSCs, with Cbp loss leading to an increase in differentiation, quiescence, and apoptosis. Genome-wide analyses of Cbp occupancy and differential gene expression upon Cbp deletion identified HSC-specific genes regulated by Cbp, providing a molecular basis for the phenotype. Finally, Cbp binding significantly overlapped at genes combinatorially bound by 7 major hematopoietic transcriptional regulators, linking Cbp to a critical HSC transcriptional regulatory network. Our data demonstrate that Cbp plays a role in adult HSC homeostasis by maintaining the balance between different HSC fate decisions, and our findings identify a putative HSC-specific transcriptional network coordinated by Cbp.

  9. Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

    Science.gov (United States)

    de Franciscis, Sebastiano; Caravagna, Giulio; Mauri, Giancarlo; D’Onofrio, Alberto

    2016-06-01

    Gene switching dynamics is a major source of randomness in genetic networks, also in the case of large concentrations of the transcription factors. In this work, we consider a common network motif - the positive feedback of a transcription factor on its own synthesis - and assess its response to extrinsic noises perturbing gene deactivation in a variety of settings where the network might operate. These settings are representative of distinct cellular types, abundance of transcription factors and ratio between gene switching and protein synthesis rates. By investigating noise-induced transitions among the different network operative states, our results suggest that gene switching rates are key parameters to shape network response to external perturbations, and that such response depends on the particular biological setting, i.e. the characteristic time scales and protein abundance. These results might have implications on our understanding of irreversible transitions for noise-related phenomena such as cellular differentiation. In addition these evidences suggest to adopt the appropriate mathematical model of the network in order to analyze the system consistently to the reference biological setting.

  10. Related pituitary cell lineages develop into interdigitated 3D cell networks.

    Science.gov (United States)

    Budry, Lionel; Lafont, Chrystel; El Yandouzi, Taoufik; Chauvet, Norbert; Conéjero, Geneviève; Drouin, Jacques; Mollard, Patrice

    2011-07-26

    The pituitary gland has long been considered to be a random patchwork of hormone-producing cells. By using pituitary-scale tridimensional imaging for two of the least abundant cell lineages, the corticotropes and gonadotropes, we have now uncovered highly organized and interdigitated cell networks that reflect homotypic and heterotypic interactions between cells. Although newly differentiated corticotrope cells appear on the ventral surface of the gland, they rapidly form homotypic strands of cells that extend from the lateral tips of the anterior pituitary along its ventral surface and into the medial gland. As the corticotrope network is established away from the microvasculature, cell morphology changes from rounded, to polygonal, and finally to cells with long cytoplasmic processes or cytonemes that connect corticotropes to the perivascular space. Gonadotropes differentiate later and are positioned in close proximity to corticotropes and capillaries. Blockade of corticotrope terminal differentiation produced by knockout of the gene encoding the transcription factor Tpit results in smaller gonadotropes within an expanded cell network, particularly in the lateral gland. Thus, pituitary-scale tridimensional imaging reveals highly structured cell networks of unique topology for each pituitary lineage. The sequential development of interdigitated cell networks during organogenesis indicate that extensive cell:cell interactions lead to a highly ordered cell positioning rather than random patchwork.

  11. Small Cell Network Topology Comparison

    Directory of Open Access Journals (Sweden)

    Jan Oppolzer

    2013-01-01

    Full Text Available One of the essential problems in a mobile network with small cells is that there is only a limited number of (PCIs available. Due to this fact, operators face the inevitable need for reusing (PCIs. In our contribution, we are dealing with a (PCI assignment to FAPs in three different topologies. The first model places FAPs randomly within the network while respecting overlapping defined. The second model places FAPs in a grid without other restrictions. The third model forms a grid as well, although buildings and roads are taken into account and (FAPs are always inside buildings. The proposed models are compared and a conclusion is made based on simulation results.

  12. Noise Effects on Oscillator Network of Transcription Regulators

    Institute of Scientific and Technical Information of China (English)

    WANG Xian-Ju; AI Bao-Quan; LIU Guo-Tao; LIU Liang-Gang

    2002-01-01

    Based on the model describing the regulation of the PRM operator region of λ phage proposed by Jeff Hastyet al., we study the noise effects on the oscillator network. We find that the additive noise cannot change the period andthe amplitude of the relaxation oscillator, but in the multiplicative case, the period of the relaxation oscillator increasesto a constant value with the increase of the strength of noise, and the amplitude of the relaxation oscillator also showsincreases with the increase of the strength of noise. This novel results suggest that an external multiplicative noise sourcecould be used to control gene expression.

  13. Coevolution within a transcriptional network by compensatory trans and cis mutations

    KAUST Repository

    Kuo, D.

    2010-10-26

    Transcriptional networks have been shown to evolve very rapidly, prompting questions as to how such changes arise and are tolerated. Recent comparisons of transcriptional networks across species have implicated variations in the cis-acting DNA sequences near genes as the main cause of divergence. What is less clear is how these changes interact with trans-acting changes occurring elsewhere in the genetic circuit. Here, we report the discovery of a system of compensatory trans and cis mutations in the yeast AP-1 transcriptional network that allows for conserved transcriptional regulation despite continued genetic change. We pinpoint a single species, the fungal pathogen Candida glabrata, in which a trans mutation has occurred very recently in a single AP-1 family member, distinguishing it from its Saccharomyces ortholog. Comparison of chromatin immunoprecipitation profiles between Candida and Saccharomyces shows that, despite their different DNA-binding domains, the AP-1 orthologs regulate a conserved block of genes. This conservation is enabled by concomitant changes in the cis-regulatory motifs upstream of each gene. Thus, both trans and cis mutations have perturbed the yeast AP-1 regulatory system in such a way as to compensate for one another. This demonstrates an example of “coevolution” between a DNA-binding transcription factor and its cis-regulatory site, reminiscent of the coevolution of protein binding partners.

  14. A network of paralogous stress response transcription factors in the human pathogen Candida glabrata.

    Directory of Open Access Journals (Sweden)

    Jawad eMerhej

    2016-05-01

    Full Text Available The yeast Candida glabrata has become the second cause of systemic candidemia in humans. However, relatively few genome-wide studies have been conducted in this organism and our knowledge of its transcriptional regulatory network is quite limited. In the present work, we combined genome-wide chromatin immunoprecipitation (ChIP-seq, transcriptome analyses and DNA binding motif predictions to describe the regulatory interactions of the seven Yap (Yeast AP1 transcription factors of C. glabrata. We described a transcriptional network containing 255 regulatory interactions and 309 potential target genes. We predicted with high confidence the preferred DNA binding sites for 5 of the 7 CgYaps and showed a strong conservation of the Yap DNA binding properties between S. cerevisiae and C. glabrata. We provided reliable functional annotation for 3 of the 7 Yaps and identified for Yap1 and Yap5 a core regulon which is conserved in S. cerevisiae, C. glabrata and C. albicans. We uncovered new roles for CgYap7 in the regulation of iron-sulfur cluster biogenesis, for CgYap1 in the regulation of heme biosynthesis and for CgYap5 in the repression of GRX4 in response to iron starvation. These transcription factors define an interconnected transcriptional network at the cross-roads between redox homeostasis, oxygen consumption and iron metabolism.

  15. Identifying significant genetic regulatory networks in the prostate cancer from microarray data based on transcription factor analysis and conditional independency

    Directory of Open Access Journals (Sweden)

    Yeh Cheng-Yu

    2009-12-01

    Full Text Available Abstract Background Prostate cancer is a world wide leading cancer and it is characterized by its aggressive metastasis. According to the clinical heterogeneity, prostate cancer displays different stages and grades related to the aggressive metastasis disease. Although numerous studies used microarray analysis and traditional clustering method to identify the individual genes during the disease processes, the important gene regulations remain unclear. We present a computational method for inferring genetic regulatory networks from micorarray data automatically with transcription factor analysis and conditional independence testing to explore the potential significant gene regulatory networks that are correlated with cancer, tumor grade and stage in the prostate cancer. Results To deal with missing values in microarray data, we used a K-nearest-neighbors (KNN algorithm to determine the precise expression values. We applied web services technology to wrap the bioinformatics toolkits and databases to automatically extract the promoter regions of DNA sequences and predicted the transcription factors that regulate the gene expressions. We adopt the microarray datasets consists of 62 primary tumors, 41 normal prostate tissues from Stanford Microarray Database (SMD as a target dataset to evaluate our method. The predicted results showed that the possible biomarker genes related to cancer and denoted the androgen functions and processes may be in the development of the prostate cancer and promote the cell death in cell cycle. Our predicted results showed that sub-networks of genes SREBF1, STAT6 and PBX1 are strongly related to a high extent while ETS transcription factors ELK1, JUN and EGR2 are related to a low extent. Gene SLC22A3 may explain clinically the differentiation associated with the high grade cancer compared with low grade cancer. Enhancer of Zeste Homolg 2 (EZH2 regulated by RUNX1 and STAT3 is correlated to the pathological stage

  16. The Switch of the Transcriptional Network with REST and miR-21 in Embryonic Stem Cells and Its Robustness Analysis%包含RE1沉默转录因子和miR-21的胚胎干细胞调控网络的双稳开关及鲁棒性的研究

    Institute of Scientific and Technical Information of China (English)

    贺勤斌; 郝军军; 蔡水明; 王瑞琦; 刘曾荣

    2011-01-01

    In this paper; we present a computational model for the transcriptional network in embryonic stem cells (ESCs) involving the REST (RE1-silencing transcription factor); miR-21; and the transcription factors OCT4; SOX2 and NANOG. The model suggests that there is a bistable switch in the transcription network and shows that REST and miR-21 play critical roles in dynamics of the switch. Specifically; changing the concentration of REST or miR-21 will lead to the shift of bistable switching curve; as well as the changes in length of bistable region. At the same time; the relationship between two external input signals; A and B; and the robustness of the switch are also discussed. It is shown that a more robust switch can be obtained through appropriate combination of the two external signals. In addition; the model suggests that the main role of external input A is to maintain self-renewal and pluripotency of ESCs. In contrast; the external input B plays a key role in increasing robustness of the switch.%建立了包含RE1沉默转录因子(RE1-silencing transcription factor,REST)和miR-21,以及转录因子OCT4、SOX2和NANOG的胚胎干细胞(ES细胞)核心调控网络的数学模型,证明该调控网络存在双稳开关,并分析了REST和miR-21对双稳开关的影响,发现改变REST或miR-21的浓度,会引起双稳开关曲线的平移及双稳区域长度的变化.同时,还讨论了胚胎干细胞调控网络的两种外部输入信号A和B与双稳开关鲁棒性的关系,结果表明,通过适当地组合两种外部输入信号,能够得到更加鲁棒的双稳开关.我们推测,信号A在维持正常ES细胞的自我更新及分化中起主要作用,信号B则在维持胚胎干细胞调控网络的鲁棒性中超重要作用.

  17. Constrained transcription factor spacing is prevalent and important for transcriptional control of mouse blood cells.

    Science.gov (United States)

    Ng, Felicia S L; Schütte, Judith; Ruau, David; Diamanti, Evangelia; Hannah, Rebecca; Kinston, Sarah J; Göttgens, Berthold

    2014-12-16

    Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the 'enhanceosome' versus the 'TF collective' model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary. We developed a motif-pair discovery pipeline to identify motif co-occurrences with preferential distance(s) between motifs in TF-bound regions. Utilizing a compendium of 289 mouse haematopoietic TF ChIP-seq datasets, we demonstrate that haematopoietic-related motif-pairs commonly occur with highly conserved constrained spacing and orientation between motifs. Furthermore, motif clustering revealed specific associations for both heterotypic and homotypic motif-pairs with particular haematopoietic cell types. We also showed that disrupting the spacing between motif-pairs significantly affects transcriptional activity in a well-known motif-pair-E-box and GATA, and in two previously unknown motif-pairs with constrained spacing-Ets and Homeobox as well as Ets and E-box. In this study, we provide evidence for widespread sequence-specific TF pair interaction with DNA that conforms to the 'enhanceosome' model, and furthermore identify associations between specific haematopoietic cell-types and motif-pairs. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  18. Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma

    DEFF Research Database (Denmark)

    Cinegaglia, Naiara C; Andrade, Sonia Cristina S; Tokar, Tomas;

    2016-01-01

    of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma....

  19. Architecture of transcriptional regulatory circuits is knitted over the topology of bio-molecular interaction networks

    Directory of Open Access Journals (Sweden)

    Nielsen Jens

    2008-02-01

    Full Text Available Abstract Background Uncovering the operating principles underlying cellular processes by using 'omics' data is often a difficult task due to the high-dimensionality of the solution space that spans all interactions among the bio-molecules under consideration. A rational way to overcome this problem is to use the topology of bio-molecular interaction networks in order to constrain the solution space. Such approaches systematically integrate the existing biological knowledge with the 'omics' data. Results Here we introduce a hypothesis-driven method that integrates bio-molecular network topology with transcriptome data, thereby allowing the identification of key biological features (Reporter Features around which transcriptional changes are significantly concentrated. We have combined transcriptome data with different biological networks in order to identify Reporter Gene Ontologies, Reporter Transcription Factors, Reporter Proteins and Reporter Complexes, and use this to decipher the logic of regulatory circuits playing a key role in yeast glucose repression and human diabetes. Conclusion Reporter Features offer the opportunity to identify regulatory hot-spots in bio-molecular interaction networks that are significantly affected between or across conditions. Results of the Reporter Feature analysis not only provide a snapshot of the transcriptional regulatory program but also are biologically easy to interpret and provide a powerful way to generate new hypotheses. Our Reporter Features analyses of yeast glucose repression and human diabetes data brings hints towards the understanding of the principles of transcriptional regulation controlling these two important and potentially closely related systems.

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

    Directory of Open Access Journals (Sweden)

    Tauch Andreas

    2009-01-01

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

  1. Intracompartmental and intercompartmental transcriptional networks coordinate the expression of genes for organellar functions.

    Science.gov (United States)

    Leister, Dario; Wang, Xi; Haberer, Georg; Mayer, Klaus F X; Kleine, Tatjana

    2011-09-01

    Genes for mitochondrial and chloroplast proteins are distributed between the nuclear and organellar genomes. Organelle biogenesis and metabolism, therefore, require appropriate coordination of gene expression in the different compartments to ensure efficient synthesis of essential multiprotein complexes of mixed genetic origin. Whereas organelle-to-nucleus signaling influences nuclear gene expression at the transcriptional level, organellar gene expression (OGE) is thought to be primarily regulated posttranscriptionally. Here, we show that intracompartmental and intercompartmental transcriptional networks coordinate the expression of genes for organellar functions. Nearly 1,300 ATH1 microarray-based transcriptional profiles of nuclear and organellar genes for mitochondrial and chloroplast proteins in the model plant Arabidopsis (Arabidopsis thaliana) were analyzed. The activity of genes involved in organellar energy production (OEP) or OGE in each of the organelles and in the nucleus is highly coordinated. Intracompartmental networks that link the OEP and OGE gene sets serve to synchronize the expression of nucleus- and organelle-encoded proteins. At a higher regulatory level, coexpression of organellar and nuclear OEP/OGE genes typically modulates chloroplast functions but affects mitochondria only when chloroplast functions are perturbed. Under conditions that induce energy shortage, the intercompartmental coregulation of photosynthesis genes can even override intracompartmental networks. We conclude that dynamic intracompartmental and intercompartmental transcriptional networks for OEP and OGE genes adjust the activity of organelles in response to the cellular energy state and environmental stresses, and we identify candidate cis-elements involved in the transcriptional coregulation of nuclear genes. Regarding the transcriptional regulation of chloroplast genes, novel tentative target genes of σ factors are identified.

  2. Signaling and transcriptional networks in heart development and regeneration.

    Science.gov (United States)

    Bruneau, Benoit G

    2013-03-01

    The mammalian heart is the first functional organ, the first indicator of life. Its normal formation and function are essential for fetal life. Defects in heart formation lead to congenital heart defects, underscoring the finesse with which the heart is assembled. Understanding the regulatory networks controlling heart development have led to significant insights into its lineage origins and morphogenesis and illuminated important aspects of mammalian embryology, while providing insights into human congenital heart disease. The mammalian heart has very little regenerative potential, and thus, any damage to the heart is life threatening and permanent. Knowledge of the developing heart is important for effective strategies of cardiac regeneration, providing new hope for future treatments for heart disease. Although we still have an incomplete picture of the mechanisms controlling development of the mammalian heart, our current knowledge has important implications for embryology and better understanding of human heart disease.

  3. Using cell fate attractors to uncover transcriptional regulation of HL60 neutrophil differentiation

    Directory of Open Access Journals (Sweden)

    Kauffman Stuart A

    2009-02-01

    Full Text Available Abstract Background The process of cellular differentiation is governed by complex dynamical biomolecular networks consisting of a multitude of genes and their products acting in concert to determine a particular cell fate. Thus, a systems level view is necessary for understanding how a cell coordinates this process and for developing effective therapeutic strategies to treat diseases, such as cancer, in which differentiation plays a significant role. Theoretical considerations and recent experimental evidence support the view that cell fates are high dimensional attractor states of the underlying molecular networks. The temporal behavior of the network states progressing toward different cell fate attractors has the potential to elucidate the underlying molecular mechanisms governing differentiation. Results Using the HL60 multipotent promyelocytic leukemia cell line, we performed experiments that ultimately led to two different cell fate attractors by two treatments of varying dosage and duration of the differentiation agent all-trans-retinoic acid (ATRA. The dosage and duration combinations of the two treatments were chosen by means of flow cytometric measurements of CD11b, a well-known early differentiation marker, such that they generated two intermediate populations that were poised at the apparently same stage of differentiation. However, the population of one treatment proceeded toward the terminally differentiated neutrophil attractor while that of the other treatment reverted back toward the undifferentiated promyelocytic attractor. We monitored the gene expression changes in the two populations after their respective treatments over a period of five days and identified a set of genes that diverged in their expression, a subset of which promotes neutrophil differentiation while the other represses cell cycle progression. By employing promoter based transcription factor binding site analysis, we found enrichment in the set of divergent

  4. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Energy Technology Data Exchange (ETDEWEB)

    Rodionov, Dmitry A.; Novichkov, Pavel; Stavrovskaya, Elena D.; Rodionova, Irina A.; Li, Xiaoqing; Kazanov, Marat D.; Ravcheev, Dmitry A.; Gerasimova, Anna V.; Kazakov, Alexey E.; Kovaleva, Galina Y.; Permina, Elizabeth A.; Laikova, Olga N.; Overbeek, Ross; Romine, Margaret F.; Fredrickson, Jim K.; Arkin, Adam P.; Dubchak, Inna; Osterman, Andrei L.; Gelfand, Mikhail S.

    2011-06-15

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. Despite the growing number of genome-scale gene expression studies, our abilities to convert the results of these studies into accurate regulatory annotations and to project them from model to other organisms are extremely limited. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. However, even orthologous regulators with conserved DNA-binding motifs may control substantially different gene sets, revealing striking differences in regulatory strategies between the Shewanella spp. and E. coli. Multiple examples of regulatory network rewiring include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), and numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. NagR for N-acetylglucosamine catabolism and PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).

  5. Divergent Evolution of the Transcriptional Network Controlled by Snf1-Interacting Protein Sip4 in Budding Yeasts.

    Science.gov (United States)

    Mehlgarten, Constance; Krijger, Jorrit-Jan; Lemnian, Ioana; Gohr, André; Kasper, Lydia; Diesing, Anne-Kathrin; Grosse, Ivo; Breunig, Karin D

    2015-01-01

    Cellular responses to starvation are of ancient origin since nutrient limitation has always been a common challenge to the stability of living systems. Hence, signaling molecules involved in sensing or transducing information about limiting metabolites are highly conserved, whereas transcription factors and the genes they regulate have diverged. In eukaryotes the AMP-activated protein kinase (AMPK) functions as a central regulator of cellular energy homeostasis. The yeast AMPK ortholog SNF1 controls the transcriptional network that counteracts carbon starvation conditions by regulating a set of transcription factors. Among those Cat8 and Sip4 have overlapping DNA-binding specificity for so-called carbon source responsive elements and induce target genes upon SNF1 activation. To analyze the evolution of the Cat8-Sip4 controlled transcriptional network we have compared the response to carbon limitation of Saccharomyces cerevisiae to that of Kluyveromyces lactis. In high glucose, S. cerevisiae displays tumor cell-like aerobic fermentation and repression of respiration (Crabtree-positive) while K. lactis has a respiratory-fermentative life-style, respiration being regulated by oxygen availability (Crabtree-negative), which is typical for many yeasts and for differentiated higher cells. We demonstrate divergent evolution of the Cat8-Sip4 network and present evidence that a role of Sip4 in controlling anabolic metabolism has been lost in the Saccharomyces lineage. We find that in K. lactis, but not in S. cerevisiae, the Sip4 protein plays an essential role in C2 carbon assimilation including induction of the glyoxylate cycle and the carnitine shuttle genes. Induction of KlSIP4 gene expression by KlCat8 is essential under these growth conditions and a primary function of KlCat8. Both KlCat8 and KlSip4 are involved in the regulation of lactose metabolism in K. lactis. In chromatin-immunoprecipitation experiments we demonstrate binding of both, KlSip4 and KlCat8, to

  6. Divergent Evolution of the Transcriptional Network Controlled by Snf1-Interacting Protein Sip4 in Budding Yeasts.

    Directory of Open Access Journals (Sweden)

    Constance Mehlgarten

    Full Text Available Cellular responses to starvation are of ancient origin since nutrient limitation has always been a common challenge to the stability of living systems. Hence, signaling molecules involved in sensing or transducing information about limiting metabolites are highly conserved, whereas transcription factors and the genes they regulate have diverged. In eukaryotes the AMP-activated protein kinase (AMPK functions as a central regulator of cellular energy homeostasis. The yeast AMPK ortholog SNF1 controls the transcriptional network that counteracts carbon starvation conditions by regulating a set of transcription factors. Among those Cat8 and Sip4 have overlapping DNA-binding specificity for so-called carbon source responsive elements and induce target genes upon SNF1 activation. To analyze the evolution of the Cat8-Sip4 controlled transcriptional network we have compared the response to carbon limitation of Saccharomyces cerevisiae to that of Kluyveromyces lactis. In high glucose, S. cerevisiae displays tumor cell-like aerobic fermentation and repression of respiration (Crabtree-positive while K. lactis has a respiratory-fermentative life-style, respiration being regulated by oxygen availability (Crabtree-negative, which is typical for many yeasts and for differentiated higher cells. We demonstrate divergent evolution of the Cat8-Sip4 network and present evidence that a role of Sip4 in controlling anabolic metabolism has been lost in the Saccharomyces lineage. We find that in K. lactis, but not in S. cerevisiae, the Sip4 protein plays an essential role in C2 carbon assimilation including induction of the glyoxylate cycle and the carnitine shuttle genes. Induction of KlSIP4 gene expression by KlCat8 is essential under these growth conditions and a primary function of KlCat8. Both KlCat8 and KlSip4 are involved in the regulation of lactose metabolism in K. lactis. In chromatin-immunoprecipitation experiments we demonstrate binding of both, KlSip4 and

  7. [Immunoglobulin genes in lymphoid cells and regulation of their transcription].

    Science.gov (United States)

    Stepchenko, A G; Urakov, D N; Luchina, N N; Deev, S M; Polianovskiĭ, O L

    1990-01-01

    The hybridoma genomes contain polyploid sets of immunoglobulin genes. We have shown, that the hybridoma PTF-02 genome contains three genes of heavy chains and two genes of light chains. The genes responsible for antibody synthesis were cloned and their structure were determined. Investigation of the kappa gene transcription and its fragments which contain regulatory sequences revealed a nuclear factor. The latter interacts with the octanucleotide localized at the promoter region of the kappa gene. The purified factor activates the transcription of the kappa gene in a heterologous cell-free system. Together with the tissue-specific factor there is also an universal factor interacting with the octanucleotide sequence. We have shown an additional factor in lymphoid cells interact with the protein which binds to the octanucleotide sequence. We have shown an additional factor in lymphoid cells interacting with the protein which binds to the octanucleotide sequence. As a result, there is a family of factors which interact with ATTTGCAT sequence. One major factor (m.w. 60 +/- 2 kDa) is an obligatory component for the initiation of immunoglobulin genes transcription.

  8. Identification of a dynamic core transcriptional network in t(8;21) AML that regulates differentiation block and self-renewal.

    Science.gov (United States)

    Ptasinska, Anetta; Assi, Salam A; Martinez-Soria, Natalia; Imperato, Maria Rosaria; Piper, Jason; Cauchy, Pierre; Pickin, Anna; James, Sally R; Hoogenkamp, Maarten; Williamson, Dan; Wu, Mengchu; Tenen, Daniel G; Ott, Sascha; Westhead, David R; Cockerill, Peter N; Heidenreich, Olaf; Bonifer, Constanze

    2014-09-25

    Oncogenic transcription factors such as RUNX1/ETO, which is generated by the chromosomal translocation t(8;21), subvert normal blood cell development by impairing differentiation and driving malignant self-renewal. Here, we use digital footprinting and chromatin immunoprecipitation sequencing (ChIP-seq) to identify the core RUNX1/ETO-responsive transcriptional network of t(8;21) cells. We show that the transcriptional program underlying leukemic propagation is regulated by a dynamic equilibrium between RUNX1/ETO and RUNX1 complexes, which bind to identical DNA sites in a mutually exclusive fashion. Perturbation of this equilibrium in t(8;21) cells by RUNX1/ETO depletion leads to a global redistribution of transcription factor complexes within preexisting open chromatin, resulting in the formation of a transcriptional network that drives myeloid differentiation. Our work demonstrates on a genome-wide level that the extent of impaired myeloid differentiation in t(8;21) is controlled by the dynamic balance between RUNX1/ETO and RUNX1 activities through the repression of transcription factors that drive differentiation.

  9. Identification of a Dynamic Core Transcriptional Network in t(8;21 AML that Regulates Differentiation Block and Self-Renewal

    Directory of Open Access Journals (Sweden)

    Anetta Ptasinska

    2014-09-01

    Full Text Available Oncogenic transcription factors such as RUNX1/ETO, which is generated by the chromosomal translocation t(8;21, subvert normal blood cell development by impairing differentiation and driving malignant self-renewal. Here, we use digital footprinting and chromatin immunoprecipitation sequencing (ChIP-seq to identify the core RUNX1/ETO-responsive transcriptional network of t(8;21 cells. We show that the transcriptional program underlying leukemic propagation is regulated by a dynamic equilibrium between RUNX1/ETO and RUNX1 complexes, which bind to identical DNA sites in a mutually exclusive fashion. Perturbation of this equilibrium in t(8;21 cells by RUNX1/ETO depletion leads to a global redistribution of transcription factor complexes within preexisting open chromatin, resulting in the formation of a transcriptional network that drives myeloid differentiation. Our work demonstrates on a genome-wide level that the extent of impaired myeloid differentiation in t(8;21 is controlled by the dynamic balance between RUNX1/ETO and RUNX1 activities through the repression of transcription factors that drive differentiation.

  10. Making a tooth: growth factors, transcription factors, and stem cells

    Institute of Scientific and Technical Information of China (English)

    Yah Ding ZHANG; Zhi CHEN; Yi Qiang SONG; Chao LIU; Yi Ping CHEN

    2005-01-01

    Mammalian tooth development is largely dependent on sequential and reciprocal epithelial-mesenchymal interactions.These processes involve a series of inductive and permissive interactions that result in the determination, differentiation,and organization of odontogenic tissues. Multiple signaling molecules, including BMPs, FGFs, Shh, and Wnt proteins,have been implicated in mediating these tissue interactions. Transcription factors participate in epithelial-mesenchymal interactions via linking the signaling loops between tissue layers by responding to inductive signals and regulating the expression of other signaling molecules. Adult stem cells are highly plastic and multipotent. These cells including dental pulp stem cells and bone marrow stromal cells could be reprogrammed into odontogenic fate and participated in tooth formation. Recent progress in the studies of molecular basis of tooth development, adult stem cell biology, and regeneration will provide fundamental knowledge for the realization of human tooth regeneration in the near future.

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

    Directory of Open Access Journals (Sweden)

    Joshi Anagha

    2009-05-01

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

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

    Science.gov (United States)

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

    2008-04-01

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

  13. The BAF complex interacts with Pax6 in adult neural progenitors to establish a neurogenic cross-regulatory transcriptional network.

    Science.gov (United States)

    Ninkovic, Jovica; Steiner-Mezzadri, Andrea; Jawerka, Melanie; Akinci, Umut; Masserdotti, Giacomo; Petricca, Stefania; Fischer, Judith; von Holst, Alexander; Beckers, Johanes; Lie, Chichung D; Petrik, David; Miller, Erik; Tang, Jiong; Wu, Jiang; Lefebvre, Veronique; Demmers, Jeroen; Eisch, Amelia; Metzger, Daniel; Crabtree, Gerald; Irmler, Martin; Poot, Raymond; Götz, Magdalena

    2013-10-03

    Numerous transcriptional regulators of neurogenesis have been identified in the developing and adult brain, but how neurogenic fate is programmed at the epigenetic level remains poorly defined. Here, we report that the transcription factor Pax6 directly interacts with the Brg1-containing BAF complex in adult neural progenitors. Deletion of either Brg1 or Pax6 in the subependymal zone (SEZ) causes the progeny of adult neural stem cells to convert to the ependymal lineage within the SEZ while migrating neuroblasts convert to different glial lineages en route to or in the olfactory bulb (OB). Genome-wide analyses reveal that the majority of genes downregulated in the Brg1 null SEZ and OB contain Pax6 binding sites and are also downregulated in Pax6 null SEZ and OB. Downstream of the Pax6-BAF complex, we find that Sox11, Nfib, and Pou3f4 form a transcriptional cross-regulatory network that drives neurogenesis and can convert postnatal glia into neurons. Taken together, elements of our work identify a tripartite effector network activated by Pax6-BAF that programs neuronal fate.

  14. Integrative analysis of the zinc finger transcription factor Lame duck in the Drosophila myogenic gene regulatory network.

    Science.gov (United States)

    Busser, Brian W; Huang, Di; Rogacki, Kevin R; Lane, Elizabeth A; Shokri, Leila; Ni, Ting; Gamble, Caitlin E; Gisselbrecht, Stephen S; Zhu, Jun; Bulyk, Martha L; Ovcharenko, Ivan; Michelson, Alan M

    2012-12-11

    Contemporary high-throughput technologies permit the rapid identification of transcription factor (TF) target genes on a genome-wide scale, yet the functional significance of TFs requires knowledge of target gene expression patterns, cooperating TFs, and cis-regulatory element (CRE) structures. Here we investigated the myogenic regulatory network downstream of the Drosophila zinc finger TF Lame duck (Lmd) by combining both previously published and newly performed genomic data sets, including ChIP sequencing (ChIP-seq), genome-wide mRNA profiling, cell-specific expression patterns of putative transcriptional targets, analysis of histone mark signatures, studies of TF cooccupancy by additional mesodermal regulators, TF binding site determination using protein binding microarrays (PBMs), and machine learning of candidate CRE motif compositions. Our findings suggest that Lmd orchestrates an extensive myogenic regulatory network, a conclusion supported by the identification of Lmd-dependent genes, histone signatures of Lmd-bound genomic regions, and the relationship of these features to cell-specific gene expression patterns. The heterogeneous cooccupancy of Lmd-bound regions with additional mesodermal regulators revealed that different transcriptional inputs are used to mediate similar myogenic gene expression patterns. Machine learning further demonstrated diverse combinatorial motif patterns within tissue-specific Lmd-bound regions. PBM analysis established the complete spectrum of Lmd DNA binding specificities, and site-directed mutagenesis of Lmd and additional newly discovered motifs in known enhancers demonstrated the critical role of these TF binding sites in supporting full enhancer activity. Collectively, these findings provide insights into the transcriptional codes regulating muscle gene expression and offer a generalizable approach for similar studies in other systems.

  15. A role for RNA post-transcriptional regulation in satellite cell activation

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    Farina Nicholas H

    2012-10-01

    Full Text Available Abstract Background Satellite cells are resident skeletal muscle stem cells responsible for muscle maintenance and repair. In resting muscle, satellite cells are maintained in a quiescent state. Satellite cell activation induces the myogenic commitment factor, MyoD, and cell cycle entry to facilitate transition to a population of proliferating myoblasts that eventually exit the cycle and regenerate muscle tissue. The molecular mechanism involved in the transition of a quiescent satellite cell to a transit-amplifying myoblast is poorly understood. Methods Satellite cells isolated by FACS from uninjured skeletal muscle and 12 h post-muscle injury from wild type and Syndecan-4 null mice were probed using Affymetrix 430v2 gene chips and analyzed by Spotfiretm and Ingenuity Pathway analysis to identify gene expression changes and networks associated with satellite cell activation, respectively. Additional analyses of target genes identify miRNAs exhibiting dynamic changes in expression during satellite cell activation. The function of the miRNAs was assessed using miRIDIAN hairpin inhibitors. Results An unbiased gene expression screen identified over 4,000 genes differentially expressed in satellite cells in vivo within 12 h following muscle damage and more than 50% of these decrease dramatically. RNA binding proteins and genes involved in post-transcriptional regulation were significantly over-represented whereas splicing factors were preferentially downregulated and mRNA stability genes preferentially upregulated. Furthermore, six computationally identified miRNAs demonstrated novel expression through muscle regeneration and in satellite cells. Three of the six miRNAs were found to regulate satellite cell fate. Conclusions The quiescent satellite cell is actively maintained in a state poised to activate in response to external signals. Satellite cell activation appears to be regulated by post-transcriptional gene regulation.

  16. Distinctive characteristics of transcriptional profiles from two epithelial cell lines upon interaction with Actinobacillus actinomycetemcomitans.

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    Mans, J J; Baker, H V; Oda, D; Lamont, R J; Handfield, M

    2006-08-01

    Transcriptional profiling and gene ontology analyses were performed to investigate the unique responses of two different epithelial cell lines to an Actinobacillus actinomycetemcomitans challenge. A total of 2867 genes were differentially regulated among all experimental conditions. The analysis of these 2867 genes revealed that the predominant specific response to infection in HeLa cells was associated with the regulation of enzyme activity, RNA metabolism, nucleoside and nucleic acid transport and protein modification. The predominant specific response in immortalized human gingival keratinocytes (IHGK) was associated with the regulation of angiogenesis, chemotaxis, transmembrane receptor protein tyrosine kinase signaling, cell differentiation, apoptosis and response to stress. Of particular interest, stress response genes were significantly - yet differently - affected in both cell lines. In HeLa cells, only three regulated genes impacted the response to stress, and the response to unfolded protein was the only term that passed the ontology filters. This strikingly contrasted with the profiles obtained for IHGK, in which 61 regulated genes impacted the response to stress and constituted an extensive network of cell responses to A. actinomycetemcomitans interaction (response to pathogens, oxidative stress, unfolded proteins, DNA damage, starvation and wounding). Hence, while extensive similarities were found in the transcriptional profiles of these two epithelial cell lines, significant differences were highlighted. These differences were predominantly found in pathways that are associated with host-pathogen interactions.

  17. Reshaping the transcriptional frontier: epigenetics and somatic cell nuclear transfer.

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    Long, Charles R; Westhusin, Mark E; Golding, Michael C

    2014-02-01

    Somatic-cell nuclear transfer (SCNT) experiments have paved the way to the field of cellular reprogramming. The demonstrated ability to clone over 20 different species to date has proven that the technology is robust but very inefficient, and is prone to developmental anomalies. Yet, the offspring from cloned animals exhibit none of the abnormalities of their parents, suggesting the low efficiency and high developmental mortality are epigenetic in origin. The epigenetic barriers to reprogramming somatic cells into a totipotent embryo capable of developing into a viable offspring are significant and varied. Despite their intimate relationship, chromatin structure and transcription are often not uniformly reprogramed after nuclear transfer, and many cloned embryos develop gene expression profiles that are hybrids between the donor cell and an embryonic blastomere. Recent advances in cellular reprogramming suggest that alteration of donor-cell chromatin structure towards that found in an normal embryo is actually the rate-limiting step in successful development of SCNT embryos. Here we review the literature relevant to the transformation of a somatic-cell nucleus into an embryo capable of full-term development. Interestingly, while resetting somatic transcription and associated epigenetic marks are absolutely required for development of SCNT embryos, life does not demand perfection.

  18. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

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    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  19. Sox17-Mediated XEN Cell Conversion Identifies Dynamic Networks Controlling Cell-Fate Decisions in Embryo-Derived Stem Cells

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    Angela C.H. McDonald

    2014-10-01

    Full Text Available Little is known about the gene regulatory networks (GRNs distinguishing extraembryonic endoderm (ExEn stem (XEN cells from those that maintain the extensively characterized embryonic stem cell (ESC. An intriguing network candidate is Sox17, an essential transcription factor for XEN derivation and self-renewal. Here, we show that forced Sox17 expression drives ESCs toward ExEn, generating XEN cells that contribute to ExEn when placed back into early mouse embryos. Transient Sox17 expression is sufficient to drive this fate change during which time cells transit through distinct intermediate states prior to the generation of functional XEN-like cells. To orchestrate this conversion process, Sox17 acts in autoregulatory and feedforward network motifs, regulating dynamic GRNs directing cell fate. Sox17-mediated XEN conversion helps to explain the regulation of cell-fate changes and reveals GRNs regulating lineage decisions in the mouse embryo.

  20. Identification of a ZEB2-MITF-ZEB1 transcriptional network that controls melanogenesis and melanoma progression.

    Science.gov (United States)

    Denecker, G; Vandamme, N; Akay, O; Koludrovic, D; Taminau, J; Lemeire, K; Gheldof, A; De Craene, B; Van Gele, M; Brochez, L; Udupi, G M; Rafferty, M; Balint, B; Gallagher, W M; Ghanem, G; Huylebroeck, D; Haigh, J; van den Oord, J; Larue, L; Davidson, I; Marine, J-C; Berx, G

    2014-08-01

    Deregulation of signaling pathways that control differentiation, expansion and migration of neural crest-derived melanoblasts during normal development contributes also to melanoma progression and metastasis. Although several epithelial-to-mesenchymal (EMT) transcription factors, such as zinc finger E-box binding protein 1 (ZEB1) and ZEB2, have been implicated in neural crest cell biology, little is known about their role in melanocyte homeostasis and melanoma. Here we show that mice lacking Zeb2 in the melanocyte lineage exhibit a melanoblast migration defect and, unexpectedly, a severe melanocyte differentiation defect. Loss of Zeb2 in the melanocyte lineage results in a downregulation of the Microphthalmia-associated transcription factor (Mitf) and melanocyte differentiation markers concomitant with an upregulation of Zeb1. We identify a transcriptional signaling network in which the EMT transcription factor ZEB2 regulates MITF levels to control melanocyte differentiation. Moreover, our data are also relevant for human melanomagenesis as loss of ZEB2 expression is associated with reduced patient survival.

  1. Correlating transcriptional networks with pathological complete response following neoadjuvant chemotherapy for breast cancer.

    Science.gov (United States)

    Liu, Rong; Lv, Qiao-Li; Yu, Jing; Hu, Lei; Zhang, Li-Hua; Cheng, Yu; Zhou, Hong-Hao

    2015-06-01

    We aimed to investigate the association between gene co-expression modules and responses to neoadjuvant chemotherapy in breast cancer by using a systematic biological approach. The gene expression profiles and clinico-pathological data of 508 (discovery set) and 740 (validation set) patients with breast cancer who received neoadjuvant chemotherapy were analyzed. Weighted gene co-expression network analysis was performed and identified seven co-regulated gene modules. Each module and gene signature were evaluated with logistic regression models for pathological complete response (pCR). The association between modules and pCR in each intrinsic molecular subtype was also investigated. Two transcriptional modules were correlated with tumor grade, estrogen receptor status, progesterone receptor status, and chemotherapy response in breast cancer. One module that constitutes upregulated cell proliferation genes was associated with a high probability for pCR in the whole (odds ratio (OR) = 5.20 and 3.45 in the discovery and validation datasets, respectively), luminal B, and basal-like subtypes. The prognostic potentials of novel genes, such as MELK, and pCR-related genes, such as ESR1 and TOP2A, were identified. The upregulation of another gene co-expression module was associated with weak chemotherapy responses (OR = 0.19 and 0.33 in the discovery and validation datasets, respectively). The novel gene CA12 was identified as a potential prognostic indicator in this module. A systems biology network-based approach may facilitate the discovery of biomarkers for predicting chemotherapy responses in breast cancer and contribute in developing personalized medicines.

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

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    Santillán Moisés

    2008-01-01

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

  3. Transcriptional networks regulating the costamere, sarcomere, and other cytoskeletal structures in striated muscle.

    Science.gov (United States)

    Estrella, Nelsa L; Naya, Francisco J

    2014-05-01

    Structural abnormalities in striated muscle have been observed in numerous transcription factor gain- and loss-of-function phenotypes in animal and cell culture model systems, indicating that transcription is important in regulating the cytoarchitecture. While most characterized cytoarchitectural defects are largely indistinguishable by histological and ultrastructural criteria, analysis of dysregulated gene expression in each mutant phenotype has yielded valuable information regarding specific structural gene programs that may be uniquely controlled by each of these transcription factors. Linking the formation and maintenance of each subcellular structure or subset of proteins within a cytoskeletal compartment to an overlapping but distinct transcription factor cohort may enable striated muscle to control cytoarchitectural function in an efficient and specific manner. Here we summarize the available evidence that connects transcription factors, those with established roles in striated muscle such as MEF2 and SRF, as well as other non-muscle transcription factors, to the regulation of a defined cytoskeletal structure. The notion that genes encoding proteins localized to the same subcellular compartment are coordinately transcriptionally regulated may prompt rationally designed approaches that target specific transcription factor pathways to correct structural defects in muscle disease.

  4. minet: A R/Bioconductor Package for Inferring Large Transcriptional Networks Using Mutual Information

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    Bontempi Gianluca

    2008-10-01

    Full Text Available Abstract Results This paper presents the R/Bioconductor package minet (version 1.1.6 which provides a set of functions to infer mutual information networks from a dataset. Once fed with a microarray dataset, the package returns a network where nodes denote genes, edges model statistical dependencies between genes and the weight of an edge quantifies the statistical evidence of a specific (e.g transcriptional gene-to-gene interaction. Four different entropy estimators are made available in the package minet (empirical, Miller-Madow, Schurmann-Grassberger and shrink as well as four different inference methods, namely relevance networks, ARACNE, CLR and MRNET. Also, the package integrates accuracy assessment tools, like F-scores, PR-curves and ROC-curves in order to compare the inferred network with a reference one. Conclusion The package minet provides a series of tools for inferring transcriptional networks from microarray data. It is freely available from the Comprehensive R Archive Network (CRAN as well as from the Bioconductor website.

  5. Gene duplication and co-evolution of G1/S transcription factor specificity in fungi are essential for optimizing cell fitness.

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    Adi Hendler

    2017-05-01

    Full Text Available Transcriptional regulatory networks play a central role in optimizing cell survival. How DNA binding domains and cis-regulatory DNA binding sequences have co-evolved to allow the expansion of transcriptional networks and how this contributes to cellular fitness remains unclear. Here we experimentally explore how the complex G1/S transcriptional network evolved in the budding yeast Saccharomyces cerevisiae by examining different chimeric transcription factor (TF complexes. Over 200 G1/S genes are regulated by either one of the two TF complexes, SBF and MBF, which bind to specific DNA binding sequences, SCB and MCB, respectively. The difference in size and complexity of the G1/S transcriptional network across yeast species makes it well suited to investigate how TF paralogs (SBF and MBF and DNA binding sequences (SCB and MCB co-evolved after gene duplication to rewire and expand the network of G1/S target genes. Our data suggests that whilst SBF is the likely ancestral regulatory complex, the ancestral DNA binding element is more MCB-like. G1/S network expansion took place by both cis- and trans- co-evolutionary changes in closely related but distinct regulatory sequences. Replacement of the endogenous SBF DNA-binding domain (DBD with that from more distantly related fungi leads to a contraction of the SBF-regulated G1/S network in budding yeast, which also correlates with increased defects in cell growth, cell size, and proliferation.

  6. Inference of transcriptional networks in Arabidopsis through conserved noncoding sequence analysis.

    Science.gov (United States)

    Van de Velde, Jan; Heyndrickx, Ken S; Vandepoele, Klaas

    2014-07-01

    Transcriptional regulation plays an important role in establishing gene expression profiles during development or in response to (a)biotic stimuli. Transcription factor binding sites (TFBSs) are the functional elements that determine transcriptional activity, and the identification of individual TFBS in genome sequences is a major goal to inferring regulatory networks. We have developed a phylogenetic footprinting approach for the identification of conserved noncoding sequences (CNSs) across 12 dicot plants. Whereas both alignment and non-alignment-based techniques were applied to identify functional motifs in a multispecies context, our method accounts for incomplete motif conservation as well as high sequence divergence between related species. We identified 69,361 footprints associated with 17,895 genes. Through the integration of known TFBS obtained from the literature and experimental studies, we used the CNSs to compile a gene regulatory network in Arabidopsis thaliana containing 40,758 interactions, of which two-thirds act through binding events located in DNase I hypersensitive sites. This network shows significant enrichment toward in vivo targets of known regulators, and its overall quality was confirmed using five different biological validation metrics. Finally, through the integration of detailed expression and function information, we demonstrate how static CNSs can be converted into condition-dependent regulatory networks, offering opportunities for regulatory gene annotation.

  7. Transcriptional analysis of phloem-associated cells of potato.

    Science.gov (United States)

    Lin, Tian; Lashbrook, Coralie C; Cho, Sung Ki; Butler, Nathaniel M; Sharma, Pooja; Muppirala, Usha; Severin, Andrew J; Hannapel, David J

    2015-09-03

    Numerous signal molecules, including proteins and mRNAs, are transported through the architecture of plants via the vascular system. As the connection between leaves and other organs, the petiole and stem are especially important in their transport function, which is carried out by the phloem and xylem, especially by the sieve elements in the phloem system. The phloem is an important conduit for transporting photosynthate and signal molecules like metabolites, proteins, small RNAs, and full-length mRNAs. Phloem sap has been used as an unadulterated source to profile phloem proteins and RNAs, but unfortunately, pure phloem sap cannot be obtained in most plant species. Here we make use of laser capture microdissection (LCM) and RNA-seq for an in-depth transcriptional profile of phloem-associated cells of both petioles and stems of potato. To expedite our analysis, we have taken advantage of the potato genome that has recently been fully sequenced and annotated. Out of the 27 k transcripts assembled that we identified, approximately 15 k were present in phloem-associated cells of petiole and stem with greater than ten reads. Among these genes, roughly 10 k are affected by photoperiod. Several RNAs from this day length-regulated group are also abundant in phloem cells of petioles and encode for proteins involved in signaling or transcriptional control. Approximately 22 % of the transcripts in phloem cells contained at least one binding motif for Pumilio, Nova, or polypyrimidine tract-binding proteins in their downstream sequences. Highlighting the predominance of binding processes identified in the gene ontology analysis of active genes from phloem cells, 78 % of the 464 RNA-binding proteins present in the potato genome were detected in our phloem transcriptome. As a reasonable alternative when phloem sap collection is not possible, LCM can be used to isolate RNA from specific cell types, and along with RNA-seq, provides practical access to expression profiles of

  8. Transcriptional Networks Controlled by NKX2-1 in the Development of Forebrain GABAergic Neurons.

    Science.gov (United States)

    Sandberg, Magnus; Flandin, Pierre; Silberberg, Shanni; Su-Feher, Linda; Price, James D; Hu, Jia Sheng; Kim, Carol; Visel, Axel; Nord, Alex S; Rubenstein, John L R

    2016-09-21

    The embryonic basal ganglia generates multiple projection neurons and interneuron subtypes from distinct progenitor domains. Combinatorial interactions of transcription factors and chromatin are thought to regulate gene expression. In the medial ganglionic eminence, the NKX2-1 transcription factor controls regional identity and, with LHX6, is necessary to specify pallidal projection neurons and forebrain interneurons. Here, we dissected the molecular functions of NKX2-1 by defining its chromosomal binding, regulation of gene expression, and epigenetic state. NKX2-1 binding at distal regulatory elements led to a repressed epigenetic state and transcriptional repression in the ventricular zone. Conversely, NKX2-1 is required to establish a permissive chromatin state and transcriptional activation in the sub-ventricular and mantle zones. Moreover, combinatorial binding of NKX2-1 and LHX6 promotes transcriptionally permissive chromatin and activates genes expressed in cortical migrating interneurons. Our integrated approach provides a foundation for elucidating transcriptional networks guiding the development of the MGE and its descendants.

  9. Parsing the Interferon Transcriptional Network and Its Disease Associations.

    Science.gov (United States)

    Mostafavi, Sara; Yoshida, Hideyuki; Moodley, Devapregasan; LeBoité, Hugo; Rothamel, Katherine; Raj, Towfique; Ye, Chun Jimmie; Chevrier, Nicolas; Zhang, Shen-Ying; Feng, Ting; Lee, Mark; Casanova, Jean-Laurent; Clark, James D; Hegen, Martin; Telliez, Jean-Baptiste; Hacohen, Nir; De Jager, Philip L; Regev, Aviv; Mathis, Diane; Benoist, Christophe

    2016-01-28

    Type 1 interferon (IFN) is a key mediator of organismal responses to pathogens, eliciting prototypical "interferon signature genes" that encode antiviral and inflammatory mediators. For a global view of IFN signatures and regulatory pathways, we performed gene expression and chromatin analyses of the IFN-induced response across a range of immunocyte lineages. These distinguished ISGs by cell-type specificity, kinetics, and sensitivity to tonic IFN and revealed underlying changes in chromatin configuration. We combined 1,398 human and mouse datasets to computationally infer ISG modules and their regulators, validated by genetic analysis in both species. Some ISGs are controlled by Stat1/2 and Irf9 and the ISRE DNA motif, but others appeared dependent on non-canonical factors. This regulatory framework helped to interpret JAK1 blockade pharmacology, different clusters being affected under tonic or IFN-stimulated conditions, and the IFN signatures previously associated with human diseases, revealing unrecognized subtleties in disease footprints, as affected by human ancestry.

  10. Microchimeric fetal cells are recruited to maternal kidney following injury and activate collagen type I transcription.

    Science.gov (United States)

    Bou-Gharios, George; Amin, Farhana; Hill, Peter; Nakamura, Hiroyuki; Maxwell, Patrick; Fisk, Nicholas M

    2011-01-01

    Fetal cells enter the maternal circulation from the early first trimester of pregnancy, where they persist in tissue decades later. We investigated in mice whether fetal microchimeric cells (FMCs) can be detected in maternal kidney, and whether they play a role in kidney homeostasis. FMCs were identified in vivo in two models: one an adaptive model following unilateral nephrectomy, the other an injury via unilateral renal ischaemia reperfusion. Both models were carried out in mothers that had been mated with transgenic mice expressing luciferase transgene under the control of collagen type I, and had given birth to either 1 or 3 litters. FMCs were detected by Y-probe fluorescent in situ hybridization (FISH) and bioluminescence, and the cell number quantified by real-time polymerase chain reaction. In the adaptive model, the remaining kidney showed more cells by all 3 parameters compared with the nephrectomized kidney, while ischaemia reperfusion resulted in higher levels of FMC participation in injured compared to contralateral kidneys. Bioluminescence showed that FMCs switch on collagen type I transcription implicating mesenchymal lineage cells. After injury, Y-probe in situ hydridization was found mainly in the tubular epithelial network. Finally, we compared FMCs with bone marrow cells and found similar dynamics but altered distribution within the kidney. We conclude that FMCs (1) are long-term sequelae of pregnancy and (2) are recruited to the kidney as a result of injury or adaptation, where they activate the transcriptional machinery of matrix proteins.

  11. Genome-Wide Mapping of Collier In Vivo Binding Sites Highlights Its Hierarchical Position in Different Transcription Regulatory Networks.

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    Mathilde de Taffin

    Full Text Available Collier, the single Drosophila COE (Collier/EBF/Olf-1 transcription factor, is required in several developmental processes, including head patterning and specification of muscle and neuron identity during embryogenesis. To identify direct Collier (Col targets in different cell types, we used ChIP-seq to map Col binding sites throughout the genome, at mid-embryogenesis. In vivo Col binding peaks were associated to 415 potential direct target genes. Gene Ontology analysis revealed a strong enrichment in proteins with DNA binding and/or transcription-regulatory properties. Characterization of a selection of candidates, using transgenic CRM-reporter assays, identified direct Col targets in dorso-lateral somatic muscles and specific neuron types in the central nervous system. These data brought new evidence that Col direct control of the expression of the transcription regulators apterous and eyes-absent (eya is critical to specifying neuronal identities. They also showed that cross-regulation between col and eya in muscle progenitor cells is required for specification of muscle identity, revealing a new parallel between the myogenic regulatory networks operating in Drosophila and vertebrates. Col regulation of eya, both in specific muscle and neuronal lineages, may illustrate one mechanism behind the evolutionary diversification of Col biological roles.

  12. Single-Cell Transcript Profiles Reveal Multilineage Priming in Early Progenitors Derived from Lgr5+ Intestinal Stem Cells

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    Tae-Hee Kim

    2016-08-01

    Full Text Available Lgr5+ intestinal stem cells (ISCs drive epithelial self-renewal, and their immediate progeny—intestinal bipotential progenitors—produce absorptive and secretory lineages via lateral inhibition. To define features of early transit from the ISC compartment, we used a microfluidics approach to measure selected stem- and lineage-specific transcripts in single Lgr5+ cells. We identified two distinct cell populations, one that expresses known ISC markers and a second, abundant population that simultaneously expresses markers of stem and mature absorptive and secretory cells. Single-molecule mRNA in situ hybridization and immunofluorescence verified expression of lineage-restricted genes in a subset of Lgr5+ cells in vivo. Transcriptional network analysis revealed that one group of Lgr5+ cells arises from the other and displays characteristics expected of bipotential progenitors, including activation of Notch ligand and cell-cycle-inhibitor genes. These findings define the earliest steps in ISC differentiation and reveal multilineage gene priming as a fundamental property of the process.

  13. Identification of regulatory network topological units coordinating the genome-wide transcriptional response to glucose in Escherichia coli

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    Gosset Guillermo

    2007-06-01

    Full Text Available Abstract Background Glucose is the preferred carbon and energy source for Escherichia coli. A complex regulatory network coordinates gene expression, transport and enzyme activities in response to the presence of this sugar. To determine the extent of the cellular response to glucose, we applied an approach combining global transcriptome and regulatory network analyses. Results Transcriptome data from isogenic wild type and crp- strains grown in Luria-Bertani medium (LB or LB + 4 g/L glucose (LB+G were analyzed to identify differentially transcribed genes. We detected 180 and 200 genes displaying increased and reduced relative transcript levels in the presence of glucose, respectively. The observed expression pattern in LB was consistent with a gluconeogenic metabolic state including active transport and interconversion of small molecules and macromolecules, induction of protease-encoding genes and a partial heat shock response. In LB+G, catabolic repression was detected for transport and metabolic interconversion activities. We also detected an increased capacity for de novo synthesis of nucleotides, amino acids and proteins. Cluster analysis of a subset of genes revealed that CRP mediates catabolite repression for most of the genes displaying reduced transcript levels in LB+G, whereas Fis participates in the upregulation of genes under this condition. An analysis of the regulatory network, in terms of topological functional units, revealed 8 interconnected modules which again exposed the importance of Fis and CRP as directly responsible for the coordinated response of the cell. This effect was also seen with other not extensively connected transcription factors such as FruR and PdhR, which showed a consistent response considering media composition. Conclusion This work allowed the identification of eight interconnected regulatory network modules that includes CRP, Fis and other transcriptional factors that respond directly or indirectly to the

  14. CARRIE web service: automated transcriptional regulatory network inference and interactive analysis.

    Science.gov (United States)

    Haverty, Peter M; Frith, Martin C; Weng, Zhiping

    2004-07-01

    We present an intuitive and interactive web service for CARRIE (Computational Ascertainment of Regulatory Relationships Inferred from Expression). CARRIE is a computational method that analyzes microarray and promoter sequence data to infer a transcriptional regulatory network from the response to a specific stimulus. This service displays an interactive graph of the inferred network and provides easy access to the evidence for the involvement of each gene in the network. We provide functionality to include network data in KEGG XML (KGML) format in this graph. Our service also provides Gene Ontology annotation to aid the user in forming hypotheses about the role of each gene in the cellular response. The CARRIE web service is freely available at http://zlab.bu.edu/CARRIE-web.

  15. Balanced transcription of cell division genes in Bacillus subtilis as revealed by single cell analysis

    NARCIS (Netherlands)

    Trip, Erik Nico; Veening, Jan-Willem; Stewart, Eric J.; Errington, Jeff; Scheffers, Dirk-Jan

    2013-01-01

    Cell division in bacteria is carried out by a set of conserved proteins that all have to function at the correct place and time. A cell cycle-dependent transcriptional programme drives cell division in bacteria such as Caulobacter crescentus. Whether such a programme exists in the Gram-positive mode

  16. Balanced transcription of cell division genes in Bacillus subtilis as revealed by single cell analysis

    NARCIS (Netherlands)

    Trip, Erik Nico; Veening, Jan-Willem; Stewart, Eric J.; Errington, Jeff; Scheffers, Dirk-Jan

    2013-01-01

    Cell division in bacteria is carried out by a set of conserved proteins that all have to function at the correct place and time. A cell cycle-dependent transcriptional programme drives cell division in bacteria such as Caulobacter crescentus. Whether such a programme exists in the Gram-positive

  17. Fast transcription rates of RNA polymerase II in human cells

    Science.gov (United States)

    Maiuri, Paolo; Knezevich, Anna; De Marco, Alex; Mazza, Davide; Kula, Anna; McNally, Jim G; Marcello, Alessandro

    2011-01-01

    Averaged estimates of RNA polymerase II (RNAPII) elongation rates in mammalian cells have been shown to range between 1.3 and 4.3 kb min−1. In this work, nascent RNAs from an integrated human immunodeficiency virus type 1-derived vector were detectable at the single living cell level by fluorescent RNA tagging. At steady state, a constant number of RNAs was measured corresponding to a minimal density of polymerases with negligible fluctuations over time. Recovery of fluorescence after photobleaching was complete within seconds, indicating a high rate of RNA biogenesis. The calculated transcription rate above 50 kb min−1 points towards a wide dynamic range of RNAPII velocities in living cells. PMID:22015688

  18. A metabolic-transcriptional network links sleep and cellular energetics in the brain.

    Science.gov (United States)

    Wisor, Jonathan P

    2012-01-01

    This review proposes a mechanistic link between cellular metabolic status, transcriptional regulatory changes and sleep. Sleep loss is associated with changes in cellular metabolic status in the brain. Metabolic sensors responsive to cellular metabolic status regulate the circadian clock transcriptional network. Modifications of the transcriptional activity of circadian clock genes affect sleep/wake state changes. Changes in sleep state reverse sleep loss-induced changes in cellular metabolic status. It is thus proposed that the regulation of circadian clock genes by cellular metabolic sensors is a critical intermediate step in the link between cellular metabolic status and sleep. Studies of this regulatory relationship may offer insights into the function of sleep at the cellular level.

  19. Model-driven mapping of transcriptional networks reveals the circuitry and dynamics of virulence regulation.

    Science.gov (United States)

    Maier, Ezekiel J; Haynes, Brian C; Gish, Stacey R; Wang, Zhuo A; Skowyra, Michael L; Marulli, Alyssa L; Doering, Tamara L; Brent, Michael R

    2015-05-01

    Key steps in understanding a biological process include identifying genes that are involved and determining how they are regulated. We developed a novel method for identifying transcription factors (TFs) involved in a specific process and used it to map regulation of the key virulence factor of a deadly fungus-its capsule. The map, built from expression profiles of 41 TF mutants, includes 20 TFs not previously known to regulate virulence attributes. It also reveals a hierarchy comprising executive, midlevel, and "foreman" TFs. When grouped by temporal expression pattern, these TFs explain much of the transcriptional dynamics of capsule induction. Phenotypic analysis of TF deletion mutants revealed complex relationships among virulence factors and virulence in mice. These resources and analyses provide the first integrated, systems-level view of capsule regulation and biosynthesis. Our methods dramatically improve the efficiency with which transcriptional networks can be analyzed, making genomic approaches accessible to laboratories focused on specific physiological processes.

  20. Acute Genome-wide effects of Rosiglitazone on PPARγ transcriptional networks in Adipocytes

    DEFF Research Database (Denmark)

    Haakonsson, Anders Kristian; Madsen, Maria Stahl; Nielsen, Ronni

    2013-01-01

    Peroxisome proliferator-activated receptor γ (PPARγ) is a master regulator of adipocyte differentiation, and genome-wide studies indicate that it is involved in the induction of most adipocyte genes. Here we report, for the first time, the acute effects of the synthetic PPARγ agonist rosiglitazone...... on the transcriptional network of PPARγ in adipocytes. Treatment with rosiglitazone for 1 hour leads to acute transcriptional activation as well as repression of a number of genes as determined by genome-wide RNA polymerase II occupancy. Unlike what has been shown for many other nuclear receptors, agonist treatment does...... not lead to major changes in the occurrence of PPARγ binding sites. However, rosiglitazone promotes PPARγ occupancy at many preexisting sites, and this is paralleled by increased occupancy of the mediator subunit MED1. The increase in PPARγ and MED1 binding is correlated with an increase in transcription...

  1. Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.

    Science.gov (United States)

    Tang, Binhua; Hsu, Hang-Kai; Hsu, Pei-Yin; Bonneville, Russell; Chen, Su-Shing; Huang, Tim H-M; Jin, Victor X

    2012-01-01

    Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network. The GO analyses revealed the distinct biological function associated with each of three embedded modules. The survival analysis showed the genes in each module were able to render a significant survival correlation in breast cancer patient cohorts. In summary, our Bayesian statistical modeling and modularity analysis not only reveals the dynamic properties of the ERα-centered regulatory network and associated distinct biological functions, but also provides a reliable and effective genomic analytical approach for the analysis of dynamic regulatory network for any given TF.

  2. Unraveling the WRKY transcription factors network in Arabidopsis Thaliana by integrative approach

    Directory of Open Access Journals (Sweden)

    Mouna Choura

    2015-06-01

    Full Text Available The WRKY transcription factors superfamily are involved in diverse biological processes in plants including response to biotic and abiotic stresses and plant immunity. Protein-protein interaction network is a useful approach for understanding these complex processes. The availability of Arabidopsis Thaliana interactome offers a good opportunity to do get a global view of protein network. In this work, we have constructed the WRKY transcription factor network by combining different sources of evidence and we characterized its topological features using computational tools. We found that WRKY network is a hub-based network involving multifunctional proteins denoted as hubs such as WRKY 70, WRKY40, WRKY 53, WRKY 60, WRKY 33 and WRKY 51. Functional annotation showed seven functional modules particularly involved in biotic stress and defense responses. Furthermore, the gene ontology and pathway enrichment analysis revealed that WRKY proteins are mainly involved in plant-pathogen interaction pathways and their functions are directly related to the stress response and immune system process.

  3. Deciphering transcriptional and metabolic networks associated with lysine metabolism during Arabidopsis seed development.

    Science.gov (United States)

    Angelovici, Ruthie; Fait, Aaron; Zhu, Xiaohong; Szymanski, Jedrzej; Feldmesser, Ester; Fernie, Alisdair R; Galili, Gad

    2009-12-01

    In order to elucidate transcriptional and metabolic networks associated with lysine (Lys) metabolism, we utilized developing Arabidopsis (Arabidopsis thaliana) seeds as a system in which Lys synthesis could be stimulated developmentally without application of chemicals and coupled this to a T-DNA insertion knockout mutation impaired in Lys catabolism. This seed-specific metabolic perturbation stimulated Lys accumulation starting from the initiation of storage reserve accumulation. Our results revealed that the response of seed metabolism to the inducible alteration of Lys metabolism was relatively minor; however, that which was observable operated in a modular manner. They also demonstrated that Lys metabolism is strongly associated with the operation of the tricarboxylic acid cycle while largely disconnected from other metabolic networks. In contrast, the inducible alteration of Lys metabolism was strongly associated with gene networks, stimulating the expression of hundreds of genes controlling anabolic processes that are associated with plant performance and vigor while suppressing a small number of genes associated with plant stress interactions. The most pronounced effect of the developmentally inducible alteration of Lys metabolism was an induction of expression of a large set of genes encoding ribosomal proteins as well as genes encoding translation initiation and elongation factors, all of which are associated with protein synthesis. With respect to metabolic regulation, the inducible alteration of Lys metabolism was primarily associated with altered expression of genes belonging to networks of amino acids and sugar metabolism. The combined data are discussed within the context of network interactions both between and within metabolic and transcriptional control systems.

  4. Transcriptional profiling of rhesus monkey embryonic stem cells.

    Science.gov (United States)

    Byrne, James A; Mitalipov, Shoukhrat M; Clepper, Lisa; Wolf, Don P

    2006-12-01

    Embryonic stem cells (ESCs) may be able to cure or alleviate the symptoms of various degenerative diseases. However, unresolved issues regarding survival, functionality, and tumor formation mean a prudent approach should be adopted towards advancing ESCs into human clinical trials. The rhesus monkey provides an ideal model organism for developing strategies to prevent immune rejection and test the feasibility, safety, and efficacy of ESC-based medical treatments. Transcriptional profiling of rhesus monkey ESCs provides a foundation for pre-clinical ESC research in this species. In the present study, we used microarray technology, immunocytochemistry, reverse transcription polymerase chain reaction (RT-PCR) and quantitative real-time PCR (qPCR) to characterize and transcriptionally profile rhesus monkey ESCs. We identified 367 stemness gene candidates that were highly (>85%) conserved across five different ESC lines. Rhesus monkey ESC lines maintained a pluripotent undifferentiated state over a wide range of POU5F1 (also known as OCT4) expression levels, and comparisons between rhesus monkey, mouse, and human stemness genes revealed five mammalian stemness genes: CCNB1, GDF3, LEFTB, POU5F1, and NANOG. These five mammalian genes are strongly expressed in rhesus monkey, mouse, and human ESCs, albeit only in the undifferentiated state, and represent the core key mammalian stemness factors.

  5. Dissecting the Transcriptional Response to Elicitors in Vitis vinifera Cells

    Science.gov (United States)

    Belchí-Navarro, Sarai; Bru, Roque; Martínez-Zapater, José M.; Lijavetzky, Diego; Pedreño, María A.

    2014-01-01

    The high effectiveness of cyclic oligosaccharides like cyclodextrins in the production of trans-resveratrol in Vitis vinifera cell cultures is enhanced in the presence of methyl jasmonate. In order to dissect the basis of the interactions among the elicitation responses triggered by these two compounds, a transcriptional analysis of grapevine cell cultures treated with cyclodextrins and methyl jasmonate separately or in combination was carried out. The results showed that the activation of genes encoding enzymes from phenylpropanoid and stilbene biosynthesis induced by cyclodextrins alone was partially enhanced in the presence of methyl jasmonate, which correlated with their effects on trans-resveratrol production. In addition, protein translation and cell cycle regulation were more highly repressed in cells treated with cyclodextrins than in those treated with methyl jasmonate, and this response was enhanced in the combined treatment. Ethylene signalling was activated by all treatments, while jasmonate signalling and salicylic acid conjugation were activated only in the presence of methyl jasmonate and cyclodextrins, respectively. Moreover, the combined treatment resulted in a crosstalk between the signalling cascades activated by cyclodextrins and methyl jasmonate, which, in turn, provoked the activation of additional regulatory pathways involving the up-regulation of MYB15, NAC and WRKY transcription factors, protein kinases and calcium signal transducers. All these results suggest that both elicitors cause an activation of the secondary metabolism in detriment of basic cell processes like the primary metabolism or cell division. Crosstalk between cyclodextrins and methyl jasmonate-induced signalling provokes an intensification of these responses resulting in a greater trans-resveratrol production. PMID:25314001

  6. Transcriptional dysregulation in NIPBL and cohesin mutant human cells.

    Directory of Open Access Journals (Sweden)

    Jinglan Liu

    2009-05-01

    Full Text Available Cohesin regulates sister chromatid cohesion during the mitotic cell cycle with Nipped-B-Like (NIPBL facilitating its loading and unloading. In addition to this canonical role, cohesin has also been demonstrated to play a critical role in regulation of gene expression in nondividing cells. Heterozygous mutations in the cohesin regulator NIPBL or cohesin structural components SMC1A and SMC3 result in the multisystem developmental disorder Cornelia de Lange Syndrome (CdLS. Genome-wide assessment of transcription in 16 mutant cell lines from severely affected CdLS probands has identified a unique profile of dysregulated gene expression that was validated in an additional 101 samples and correlates with phenotypic severity. This profile could serve as a diagnostic and classification tool. Cohesin binding analysis demonstrates a preference for intergenic regions suggesting a cis-regulatory function mimicking that of a boundary/insulator interacting protein. However, the binding sites are enriched within the promoter regions of the dysregulated genes and are significantly decreased in CdLS proband, indicating an alternative role of cohesin as a transcription factor.

  7. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

  8. Stem cell pluripotency and transcription factor Oct4

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Mammalian cell totipotency is a subject that has fascinated scientists for generations. A long lastingquestion whether some of the somatic cells retains totipotency was answered by the cloning of Dolly atthe end of the 20th century. The dawn of the 21st has brought forward great expectations in harnessingthe power of totipotentcy in medicine. Through stem cell biology, it is possible to generate any parts ofthe human body by stem cell engineering. Considerable resources will be devoted to harness the untappedpotentials of stem cells in the foreseeable future which may transform medicine as we know today. At themolecular level, totipotency has been linked to a singular transcription factor and its expression appearsto define whether a cell should be totipotent. Named Oct4, it can activate or repress the expression ofvarious genes. Curiously, very little is known about Oct4 beyond its ability to regulate gene expression. Themechanism by which Oct4 specifies totipotency remains entirely unresolved. In this review, we summarizethe structure and function of Oct4 and address issues related to Oct4 function in maintaining totipotencyor pluripotency of embryonic stem cells.

  9. Simultaneous transcriptional profiling of bacteria and their host cells.

    Directory of Open Access Journals (Sweden)

    Michael S Humphrys

    Full Text Available We developed an RNA-Seq-based method to simultaneously capture prokaryotic and eukaryotic expression profiles of cells infected with intracellular bacteria. As proof of principle, this method was applied to Chlamydia trachomatis-infected epithelial cell monolayers in vitro, successfully obtaining transcriptomes of both C. trachomatis and the host cells at 1 and 24 hours post-infection. Chlamydiae are obligate intracellular bacterial pathogens that cause a range of mammalian diseases. In humans chlamydiae are responsible for the most common sexually transmitted bacterial infections and trachoma (infectious blindness. Disease arises by adverse host inflammatory reactions that induce tissue damage & scarring. However, little is known about the mechanisms underlying these outcomes. Chlamydia are genetically intractable as replication outside of the host cell is not yet possible and there are no practical tools for routine genetic manipulation, making genome-scale approaches critical. The early timeframe of infection is poorly understood and the host transcriptional response to chlamydial infection is not well defined. Our simultaneous RNA-Seq method was applied to a simplified in vitro model of chlamydial infection. We discovered a possible chlamydial strategy for early iron acquisition, putative immune dampening effects of chlamydial infection on the host cell, and present a hypothesis for Chlamydia-induced fibrotic scarring through runaway positive feedback loops. In general, simultaneous RNA-Seq helps to reveal the complex interplay between invading bacterial pathogens and their host mammalian cells and is immediately applicable to any bacteria/host cell interaction.

  10. Transcription network construction for large-scale microarray datasets using a high-performance computing approach

    OpenAIRE

    Wu Qishi; Zhu Mengxia

    2008-01-01

    Abstract Background The advance in high-throughput genomic technologies including microarrays has demonstrated the potential of generating a tremendous amount of gene expression data for the entire genome. Deciphering transcriptional networks that convey information on intracluster correlations and intercluster connections of genes is a crucial analysis task in the post-sequence era. Most of the existing analysis methods for genome-wide gene expression profiles consist of several steps that o...

  11. GAM: a web-service for integrated transcriptional and metabolic network analysis.

    Science.gov (United States)

    Sergushichev, Alexey A; Loboda, Alexander A; Jha, Abhishek K; Vincent, Emma E; Driggers, Edward M; Jones, Russell G; Pearce, Edward J; Artyomov, Maxim N

    2016-07-08

    Novel techniques for high-throughput steady-state metabolomic profiling yield information about changes of nearly thousands of metabolites. Such metabolomic profiles, when analyzed together with transcriptional profiles, can reveal novel insights about underlying biological processes. While a number of conceptual approaches have been developed for data integration, easily accessible tools for integrated analysis of mammalian steady-state metabolomic and transcriptional data are lacking. Here we present GAM ('genes and metabolites'): a web-service for integrated network analysis of transcriptional and steady-state metabolomic data focused on identification of the most changing metabolic subnetworks between two conditions of interest. In the web-service, we have pre-assembled metabolic networks for humans, mice, Arabidopsis and yeast and adapted exact solvers for an optimal subgraph search to work in the context of these metabolic networks. The output is the most regulated metabolic subnetwork of size controlled by false discovery rate parameters. The subnetworks are then visualized online and also can be downloaded in Cytoscape format for subsequent processing. The web-service is available at: https://artyomovlab.wustl.edu/shiny/gam/.

  12. Virtual mutagenesis of the yeast cyclins genetic network reveals complex dynamics of transcriptional control networks.

    Directory of Open Access Journals (Sweden)

    Eliska Vohradska

    Full Text Available Study of genetic networks has moved from qualitative description of interactions between regulators and regulated genes to the analysis of the interaction dynamics. This paper focuses on the analysis of dynamics of one particular network--the yeast cyclins network. Using a dedicated mathematical model of gene expression and a procedure for computation of the parameters of the model from experimental data, a complete numerical model of the dynamics of the cyclins genetic network was attained. The model allowed for performing virtual experiments on the network and observing their influence on the expression dynamics of the genes downstream in the regulatory cascade. Results show that when the network structure is more complicated, and the regulatory interactions are indirect, results of gene deletion are highly unpredictable. As a consequence of quantitative behavior of the genes and their connections within the network, causal relationship between a regulator and target gene may not be discovered by gene deletion. Without including the dynamics of the system into the network, its functional properties cannot be studied and interpreted correctly.

  13. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    Directory of Open Access Journals (Sweden)

    Yihan Lin

    Full Text Available Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS.

  14. c-Myc Antagonises the Transcriptional Activity of the Androgen Receptor in Prostate Cancer Affecting Key Gene Networks.

    Science.gov (United States)

    Barfeld, Stefan J; Urbanucci, Alfonso; Itkonen, Harri M; Fazli, Ladan; Hicks, Jessica L; Thiede, Bernd; Rennie, Paul S; Yegnasubramanian, Srinivasan; DeMarzo, Angelo M; Mills, Ian G

    2017-04-01

    Prostate cancer (PCa) is the most common non-cutaneous cancer in men. The androgen receptor (AR), a ligand-activated transcription factor, constitutes the main drug target for advanced cases of the disease. However, a variety of other transcription factors and signaling networks have been shown to be altered in patients and to influence AR activity. Amongst these, the oncogenic transcription factor c-Myc has been studied extensively in multiple malignancies and elevated protein levels of c-Myc are commonly observed in PCa. Its impact on AR activity, however, remains elusive. In this study, we assessed the impact of c-Myc overexpression on AR activity and transcriptional output in a PCa cell line model and validated the antagonistic effect of c-MYC on AR-targets in patient samples. We found that c-Myc overexpression partially reprogrammed AR chromatin occupancy and was associated with altered histone marks distribution, most notably H3K4me1 and H3K27me3. We found c-Myc and the AR co-occupy a substantial number of binding sites and these exhibited enhancer-like characteristics. Interestingly, c-Myc overexpression antagonised clinically relevant AR target genes. Therefore, as an example, we validated the antagonistic relationship between c-Myc and two AR target genes, KLK3 (alias PSA, prostate specific antigen), and Glycine N-Methyltransferase (GNMT), in patient samples. Our findings provide unbiased evidence that MYC overexpression deregulates the AR transcriptional program, which is thought to be a driving force in PCa. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

  15. Impact of Transcription Units rearrangement on the evolution of the regulatory network of gamma-proteobacteria

    Directory of Open Access Journals (Sweden)

    Vasconcelos Ana

    2008-03-01

    Full Text Available Abstract Background In the past years, several studies begun to unravel the structure, dynamical properties, and evolution of transcriptional regulatory networks. However, even those comparative studies that focus on a group of closely related organisms are limited by the rather scarce knowledge on regulatory interactions outside a few model organisms, such as E. coli among the prokaryotes. Results In this paper we used the information annotated in Tractor_DB (a database of regulatory networks in gamma-proteobacteria to calculate a normalized Site Orthology Score (SOS that quantifies the conservation of a regulatory link across thirty genomes of this subclass. Then we used this SOS to assess how regulatory connections have evolved in this group, and how the variation of basic regulatory connection is reflected on the structure of the chromosome. We found that individual regulatory interactions shift between different organisms, a process that may be described as rewiring the network. At this evolutionary scale (the gamma-proteobacteria subclass this rewiring process may be an important source of variation of regulatory incoming interactions for individual networks. We also noticed that the regulatory links that form feed forward motifs are conserved in a better correlated manner than triads of random regulatory interactions or pairs of co-regulated genes. Furthermore, the rewiring process that takes place at the most basic level of the regulatory network may be linked to rearrangements of genetic material within bacterial chromosomes, which change the structure of Transcription Units and therefore the regulatory connections between Transcription Factors and structural genes. Conclusion The rearrangements that occur in bacterial chromosomes-mostly inversion or horizontal gene transfer events – are important sources of variation of gene regulation at this evolutionary scale.

  16. Pluripotent stem cell transcription factors during human odontogenesis.

    Science.gov (United States)

    da Cunha, Juliana Malta; da Costa-Neves, Adriana; Kerkis, Irina; da Silva, Marcelo Cavenaghi Pereira

    2013-09-01

    Stem cells are capable of generating various cell lines and can be obtained from adult or embryonic tissues for clinical therapies. Stem cells from deciduous dental pulp are among those that are easily obtainable from adult tissues and have been widely studied because of their ability to differentiate into a variety of cell lines in the presence of various chemical mediators. We have analyze the expression of several proteins related to the differentiation and proliferative potential of cell populations that compose the tooth germ of human fetuses. We evaluate 20 human fetuses of both genders. After being paraffin-embedded, cap and bell stages of tooth germ development were subjected to immunohistochemistry for the following markers: Oct-4, Nanog, Stat-3 and Sox-2. The studied antibodies showed nuclear or cytoplasmic immunnostaining within various anatomical structures and with various degrees of expression, indicating the action of these proteins during tooth development. We conclude that the interrelationship between these transcription factors is complex and associated with self-renewal and cell differentiation. Our results suggest that the expression of Oct-4, Nanog, Sox-2 and Stat-3 are related to differentiation in ameloblasts and odontoblasts.

  17. Genome-wide analysis of differential transcriptional and epigenetic variability across human immune cell types

    DEFF Research Database (Denmark)

    Ecker, Simone; Chen, Lu; Pancaldi, Vera

    2017-01-01

    Background: A healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability. Results: We apply a novel analytical approach to measure and compare transcriptional and epigenetic v...

  18. The Roles of the Stem Cell-Controlling Sox2 Transcription Factor: from Neuroectoderm Development to Alzheimer's Disease?

    Science.gov (United States)

    Sarlak, Golmaryam; Vincent, Bruno

    2016-04-01

    Sox2 is a component of the core transcriptional regulatory network which maintains the totipotency of the cells during embryonic preimplantation period, the pluripotency of embryonic stem cells, and the multipotency of neural stem cells. This maintenance is controlled by internal loops between Sox2 and other transcription factors of the core such as Oct4, Nanog, Dax1, and Klf4, downstream proteins of extracellular ligands, epigenetic modifiers, and miRNAs. As Sox2 plays an important role in the balance between stem cells maintenance and commitment to differentiated lineages throughout the lifetime, it is supposed that Sox2 could regulate stem cells aging processes. In this review, we provide an update concerning the involvement of Sox2 in neurogenesis during normal aging and discuss its possible role in Alzheimer's disease.

  19. The core regulatory network in human cells.

    Science.gov (United States)

    Kim, Man-Sun; Kim, Dongsan; Kang, Nam Sook; Kim, Jeong-Rae

    2017-03-04

    In order to discover the common characteristics of various cell types in the human body, many researches have been conducted to find the set of genes commonly expressed in various cell types and tissues. However, the functional characteristics of a cell is determined by the complex regulatory relationships among the genes rather than by expressed genes themselves. Therefore, it is more important to identify and analyze a core regulatory network where all regulatory relationship between genes are active across all cell types to uncover the common features of various cell types. Here, based on hundreds of tissue-specific gene regulatory networks constructed by recent genome-wide experimental data, we constructed the core regulatory network. Interestingly, we found that the core regulatory network is organized by simple cascade and has few complex regulations such as feedback or feed-forward loops. Moreover, we discovered that the regulatory links from genes in the core regulatory network to genes in the peripheral regulatory network are much more abundant than the reverse direction links. These results suggest that the core regulatory network locates at the top of regulatory network and plays a role as a 'hub' in terms of information flow, and the information that is common to all cells can be modified to achieve the tissue-specific characteristics through various types of feedback and feed-forward loops in the peripheral regulatory networks. We also found that the genes in the core regulatory network are evolutionary conserved, essential and non-disease, non-druggable genes compared to the peripheral genes. Overall, our study provides an insight into how all human cells share a common function and generate tissue-specific functional traits by transmitting and processing information through regulatory network.

  20. Transformation of intestinal stem cells into gastric stem cells on loss of transcription factor Cdx2.

    Science.gov (United States)

    Simmini, Salvatore; Bialecka, Monika; Huch, Meritxell; Kester, Lennart; van de Wetering, Marc; Sato, Toshiro; Beck, Felix; van Oudenaarden, Alexander; Clevers, Hans; Deschamps, Jacqueline

    2014-12-11

    The endodermal lining of the adult gastro-intestinal tract harbours stem cells that are responsible for the day-to-day regeneration of the epithelium. Stem cells residing in the pyloric glands of the stomach and in the small intestinal crypts differ in their differentiation programme and in the gene repertoire that they express. Both types of stem cells have been shown to grow from single cells into 3D structures (organoids) in vitro. We show that single adult Lgr5-positive stem cells, isolated from small intestinal organoids, require Cdx2 to maintain their intestinal identity and are converted cell-autonomously into pyloric stem cells in the absence of this transcription factor. Clonal descendants of Cdx2(null) small intestinal stem cells enter the gastric differentiation program instead of producing intestinal derivatives. We show that the intestinal genetic programme is critically dependent on the single transcription factor encoding gene Cdx2.

  1. A comprehensive resource of interacting protein regions for refining human transcription factor networks.

    Directory of Open Access Journals (Sweden)

    Etsuko Miyamoto-Sato

    Full Text Available Large-scale data sets of protein-protein interactions (PPIs are a valuable resource for mapping and analysis of the topological and dynamic features of interactome networks. The currently available large-scale PPI data sets only contain information on interaction partners. The data presented in this study also include the sequences involved in the interactions (i.e., the interacting regions, IRs suggested to correspond to functional and structural domains. Here we present the first large-scale IR data set obtained using mRNA display for 50 human transcription factors (TFs, including 12 transcription-related proteins. The core data set (966 IRs; 943 PPIs displays a verification rate of 70%. Analysis of the IR data set revealed the existence of IRs that interact with multiple partners. Furthermore, these IRs were preferentially associated with intrinsic disorder. This finding supports the hypothesis that intrinsically disordered regions play a major role in the dynamics and diversity of TF networks through their ability to structurally adapt to and bind with multiple partners. Accordingly, this domain-based interaction resource represents an important step in refining protein interactions and networks at the domain level and in associating network analysis with biological structure and function.

  2. Prognostic transcriptional association networks: a new supervised approach based on regression trees

    Science.gov (United States)

    Nepomuceno-Chamorro, Isabel; Azuaje, Francisco; Devaux, Yvan; Nazarov, Petr V.; Muller, Arnaud; Aguilar-Ruiz, Jesús S.; Wagner, Daniel R.

    2011-01-01

    Motivation: The application of information encoded in molecular networks for prognostic purposes is a crucial objective of systems biomedicine. This approach has not been widely investigated in the cardiovascular research area. Within this area, the prediction of clinical outcomes after suffering a heart attack would represent a significant step forward. We developed a new quantitative prediction-based method for this prognostic problem based on the discovery of clinically relevant transcriptional association networks. This method integrates regression trees and clinical class-specific networks, and can be applied to other clinical domains. Results: Before analyzing our cardiovascular disease dataset, we tested the usefulness of our approach on a benchmark dataset with control and disease patients. We also compared it to several algorithms to infer transcriptional association networks and classification models. Comparative results provided evidence of the prediction power of our approach. Next, we discovered new models for predicting good and bad outcomes after myocardial infarction. Using blood-derived gene expression data, our models reported areas under the receiver operating characteristic curve above 0.70. Our model could also outperform different techniques based on co-expressed gene modules. We also predicted processes that may represent novel therapeutic targets for heart disease, such as the synthesis of leucine and isoleucine. Availability: The SATuRNo software is freely available at http://www.lsi.us.es/isanepo/toolsSaturno/. Contact: inepomuceno@us.es Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21098433

  3. Isolation of transcription factor complexes from Arabidopsis cell suspension cultures by tandem affinity purification.

    Science.gov (United States)

    Van Leene, Jelle; Eeckhout, Dominique; Persiau, Geert; Van De Slijke, Eveline; Geerinck, Jan; Van Isterdael, Gert; Witters, Erwin; De Jaeger, Geert

    2011-01-01

    Defining protein complexes is critical to virtually all aspects of cell biology because most cellular processes are regulated by stable or more dynamic protein interactions. Elucidation of the protein-protein interaction network around transcription factors is essential to fully understand their function and regulation. In the last decade, new technologies have emerged to study protein-protein interactions under near-physiological conditions. We have developed a high-throughput tandem affinity purification (TAP)/mass spectrometry (MS) platform for cell suspension cultures to analyze protein complexes in Arabidopsis thaliana. This streamlined platform follows an integrated approach comprising generic Gateway-based vectors with high cloning flexibility, the fast generation of transgenic suspension cultures, TAP adapted for plant cells, and tandem matrix-assisted laser desorption ionization MS for the identification of purified proteins. Recently, we evaluated the GS tag, originally developed to study mammalian protein complexes, that combines two IgG-binding domains of protein G with a streptavidin-binding peptide, separated by two tobacco etch virus cleavage sites. We found that this GS tag outperforms the traditional TAP tag in plant cells, regarding both specificity and complex yield. Here, we provide detailed protocols of the GS-based TAP platform that allowed us to characterize transcription factor complexes involved in signaling in response to the plant phytohormone jasmonate.

  4. Transcriptional profiling of host gene expression in chicken embryo lung cells infected with laryngotracheitis virus

    Directory of Open Access Journals (Sweden)

    Li Xianyao

    2010-07-01

    Full Text Available Abstract Background Infection by infectious laryngotracheitis virus (ILTV; gallid herpesvirus 1 causes acute respiratory diseases in chickens often with high mortality. To better understand host-ILTV interactions at the host transcriptional level, a microarray analysis was performed using 4 × 44 K Agilent chicken custom oligo microarrays. Results Microarrays were hybridized using the two color hybridization method with total RNA extracted from ILTV infected chicken embryo lung cells at 0, 1, 3, 5, and 7 days post infection (dpi. Results showed that 789 genes were differentially expressed in response to ILTV infection that include genes involved in the immune system (cytokines, chemokines, MHC, and NF-κB, cell cycle regulation (cyclin B2, CDK1, and CKI3, matrix metalloproteinases (MMPs and cellular metabolism. Differential expression for 20 out of 789 genes were confirmed by quantitative reverse transcription-PCR (qRT-PCR. A bioinformatics tool (Ingenuity Pathway Analysis used to analyze biological functions and pathways on the group of 789 differentially expressed genes revealed that 21 possible gene networks with intermolecular connections among 275 functionally identified genes. These 275 genes were classified into a number of functional groups that included cancer, genetic disorder, cellular growth and proliferation, and cell death. Conclusion The results of this study provide comprehensive knowledge on global gene expression, and biological functionalities of differentially expressed genes in chicken embryo lung cells in response to ILTV infections.

  5. Boolean Modeling Reveals the Necessity of Transcriptional Regulation for Bistability in PC12 Cell Differentiation.

    Science.gov (United States)

    Offermann, Barbara; Knauer, Steffen; Singh, Amit; Fernández-Cachón, María L; Klose, Martin; Kowar, Silke; Busch, Hauke; Boerries, Melanie

    2016-01-01

    The nerve growth factor NGF has been shown to cause cell fate decisions toward either differentiation or proliferation depending on the relative activity of downstream pERK, pAKT, or pJNK signaling. However, how these protein signals are translated into and fed back from transcriptional activity to complete cellular differentiation over a time span of hours to days is still an open question. Comparing the time-resolved transcriptome response of NGF- or EGF-stimulated PC12 cells over 24 h in combination with protein and phenotype data we inferred a dynamic Boolean model capturing the temporal sequence of protein signaling, transcriptional response and subsequent autocrine feedback. Network topology was optimized by fitting the model to time-resolved transcriptome data under MEK, PI3K, or JNK inhibition. The integrated model confirmed the parallel use of MAPK/ERK, PI3K/AKT, and JNK/JUN for PC12 cell differentiation. Redundancy of cell signaling is demonstrated from the inhibition of the different MAPK pathways. As suggested in silico and confirmed in vitro, differentiation was substantially suppressed under JNK inhibition, yet delayed only under MEK/ERK inhibition. Most importantly, we found that positive transcriptional feedback induces bistability in the cell fate switch. De novo gene expression was necessary to activate autocrine feedback that caused Urokinase-Type Plasminogen Activator (uPA) Receptor signaling to perpetuate the MAPK activity, finally resulting in the expression of late, differentiation related genes. Thus, the cellular decision toward differentiation depends on the establishment of a transcriptome-induced positive feedback between protein signaling and gene expression thereby constituting a robust control between proliferation and differentiation.

  6. Transcriptional coactivator undifferentiated embryonic cell transcription factor 1 expressed in spermatogonial stem cells: a putative marker of boar spermatogonia.

    Science.gov (United States)

    Lee, Won-Young; Lee, Kyung-Hoon; Heo, Young-Tae; Kim, Nam-Hyung; Kim, Jin-Hoi; Kim, Jae-Hwan; Moon, Sung-Hwan; Chung, Hak-Jae; Yoon, Min-Jung; Song, Hyuk

    2014-11-30

    Spermatogenesis is initiated from spermatogonial stem cells (SSCs), which are derived from gonocytes. Although some rodent SSC markers have been investigated, other species- and developmental stage-specific markers of spermatogonia have not been identified. The objective of this study was to characterize the expression of undifferentiated embryonic cell transcription factor 1 (UTF1) gene as a potential marker for spermatogonia and SSCs in the boar testis. In boar testis tissue at pre-pubertal stages (tissues collected at 5, 30, and 60 days of age), UTF1 gene expression was detected in almost all spermatogonia cells that expressed a protein gene product 9.5 (PGP9.5), and immunocytochemical analysis of isolated total testicular cells showed that 91.14% of cells staining for PGP9.5 also stained for UTF1. However, in boar testis tissue at pubertal and post-pubertal stages (tissues collected at 90, 120, 150, and 180 days of age), UTF1 was not detected in all PGP9.5-positive cells in the basement membrane. While some PGP9.5-positive cells stained for UTF1, other cells stained only for PGP9.5 or UTF1. PGP9.5, UTF1, and NANOG was assessed in in vitro cultures of pig SSCs (pSSCs) from testes collected at 5 days of age. The relative amounts of PGP9.5, NANOG, and UTF1 mRNA were greater in pSSC colonies than in testis and muscle tissue. Thus, the UTF1 gene is expressed in PGP9.5-positive spermatogonia cells of pigs at 5 days of age, and its expression is maintained in cultured pSSC colonies, suggesting that UTF1 is a putative marker for early-stage spermatogonia in the pre-pubertal pig testis. These findings will facilitate the study of spermatogenesis and applications in germ cell research.

  7. Integrative transcriptome analysis identifies deregulated microRNA-transcription factor networks in lung adenocarcinoma.

    Science.gov (United States)

    Cinegaglia, Naiara C; Andrade, Sonia Cristina S; Tokar, Tomas; Pinheiro, Maísa; Severino, Fábio E; Oliveira, Rogério A; Hasimoto, Erica N; Cataneo, Daniele C; Cataneo, Antônio J M; Defaveri, Júlio; Souza, Cristiano P; Marques, Márcia M C; Carvalho, Robson F; Coutinho, Luiz L; Gross, Jefferson L; Rogatto, Silvia R; Lam, Wan L; Jurisica, Igor; Reis, Patricia P

    2016-05-17

    Herein, we aimed at identifying global transcriptome microRNA (miRNA) changes and miRNA target genes in lung adenocarcinoma. Samples were selected as training (N = 24) and independent validation (N = 34) sets. Tissues were microdissected to obtain >90% tumor or normal lung cells, subjected to miRNA transcriptome sequencing and TaqMan quantitative PCR validation. We further integrated our data with published miRNA and mRNA expression datasets across 1,491 lung adenocarcinoma and 455 normal lung samples. We identified known and novel, significantly over- and under-expressed (p ≤ 0.01 and FDR≤0.1) miRNAs in lung adenocarcinoma compared to normal lung tissue: let-7a, miR-10a, miR-15b, miR-23b, miR-26a, miR-26b, miR-29a, miR-30e, miR-99a, miR-146b, miR-181b, miR-181c, miR-421, miR-181a, miR-574 and miR-1247. Validated miRNAs included let-7a-2, let-7a-3, miR-15b, miR-21, miR-155 and miR-200b; higher levels of miR-21 expression were associated with lower patient survival (p = 0.042). We identified a regulatory network including miR-15b and miR-155, and transcription factors with prognostic value in lung cancer. Our findings may contribute to the development of treatment strategies in lung adenocarcinoma.

  8. Diversification in the genetic architecture of gene expression and transcriptional networks in organ differentiation of Populus.

    Science.gov (United States)

    Drost, Derek R; Benedict, Catherine I; Berg, Arthur; Novaes, Evandro; Novaes, Carolina R D B; Yu, Qibin; Dervinis, Christopher; Maia, Jessica M; Yap, John; Miles, Brianna; Kirst, Matias

    2010-05-04

    A fundamental goal of systems biology is to identify genetic elements that contribute to complex phenotypes and to understand how they interact in networks predictive of system response to genetic variation. Few studies in plants have developed such networks, and none have examined their conservation among functionally specialized organs. Here we used genetical genomics in an interspecific hybrid population of the model hardwood plant Populus to uncover transcriptional networks in xylem, leaves, and roots. Pleiotropic eQTL hotspots were detected and used to construct coexpression networks a posteriori, for which regulators were predicted based on cis-acting expression regulation. Networks were shown to be enriched for groups of genes that function in biologically coherent processes and for cis-acting promoter motifs with known roles in regulating common groups of genes. When contrasted among xylem, leaves, and roots, transcriptional networks were frequently conserved in composition, but almost invariably regulated by different loci. Similarly, the genetic architecture of gene expression regulation is highly diversified among plant organs, with less than one-third of genes with eQTL detected in two organs being regulated by the same locus. However, colocalization in eQTL position increases to 50% when they are detected in all three organs, suggesting conservation in the genetic regulation is a function of ubiquitous expression. Genes conserved in their genetic regulation among all organs are primarily cis regulated (approximately 92%), whereas genes with eQTL in only one organ are largely trans regulated. Trans-acting regulation may therefore be the primary driver of differentiation in function between plant organs.

  9. Characterizing Transcriptional Networks in Male Rainbow Darter (Etheostoma caeruleum) that Regulate Testis Development over a Complete Reproductive Cycle.

    Science.gov (United States)

    Bahamonde, Paulina A; McMaster, Mark E; Servos, Mark R; Martyniuk, Christopher J; Munkittrick, Kelly R

    2016-01-01

    Intersex is a condition that has been associated with exposure to sewage effluents in male rainbow darter (Etheostoma caeruleum). To better understand changes in the transcriptome that are associated with intersex, we characterized annual changes in the testis transcriptome in wild, unexposed fish. Rainbow darter males were collected from the Grand River (Ontario, Canada) in May (spawning), August (post-spawning), October (recrudescence), January (developing) and March (pre-spawning). Histology was used to determine the proportion of spermatogenic cell types that were present during each period of testicular maturation. Regression analysis determined that the proportion of spermatozoa versus spermatocytes in all stages of development (R2 ≥ 0.58) were inversely related; however this was not the case when males were in the post-spawning period. Gene networks that were specific to the transition from developing to pre-spawning stages included nitric oxide biosynthesis, response to wounding, sperm cell function, and stem cell maintenance. The pre-spawning to spawning transition included gene networks related to amino acid import, glycogenesis, Sertoli cell proliferation, sperm capacitation, and sperm motility. The spawning to post-spawning transition included unique gene networks associated with chromosome condensation, ribosome biogenesis and assembly, and mitotic spindle assembly. Lastly, the transition from post-spawning to recrudescence included gene networks associated with egg activation, epithelial to mesenchymal transition, membrane fluidity, and sperm cell adhesion. Noteworthy was that there were a significant number of gene networks related to immune system function that were differentially expressed throughout reproduction, suggesting that immune network signalling has a prominent role in the male testis. Transcripts in the testis of post-spawning individuals showed patterns of expression that were most different for the majority of transcripts

  10. Gene Expression Patterns Define Key Transcriptional Events InCell-Cycle Regulation By cAMP And Protein Kinase A

    Energy Technology Data Exchange (ETDEWEB)

    Zambon, Alexander C.; Zhang, Lingzhi; Minovitsky, Simon; Kanter, Joan R.; Prabhakar, Shyam; Salomonis, Nathan; Vranizan, Karen; Dubchak Inna,; Conklin, Bruce R.; Insel, Paul A.

    2005-06-01

    Although a substantial number of hormones and drugs increase cellular cAMP levels, the global impact of cAMP and its major effector mechanism, protein kinase A (PKA), on gene expression is not known. Here we show that treatment of murine wild-type S49 lymphoma cells for 24 h with 8-(4-chlorophenylthio)-cAMP (8-CPTcAMP), a PKA-selective cAMP analog, alters the expression of approx equal to 4,500 of approx. equal to 13,600 unique genes. By contrast, gene expression was unaltered in Kin- S49 cells (that lack PKA) incubated with 8-CPTcAMP. Changes in mRNA and protein expression of several cell cycle regulators accompanied cAMP-induced G1-phase cell-cycle arrest of wild-type S49 cells. Within 2h, 8-CPT-cAMP altered expression of 152 genes that contain evolutionarily conserved cAMP-response elements within 5 kb of transcriptional start sites, including the circadian clock gene Per1. Thus, cAMP through its activation of PKA produces extensive transcriptional regulation in eukaryotic cells. These transcriptional networks include a primary group of cAMP-response element-containing genes and secondary networks that include the circadian clock.

  11. Comparative transcriptional profiling of human Merkel cells and Merkel cell carcinoma.

    Science.gov (United States)

    Mouchet, Nicolas; Coquart, Nolwenn; Lebonvallet, Nicolas; Le Gall-Ianotto, Christelle; Mogha, Ariane; Fautrel, Alain; Boulais, Nicholas; Dréno, Brigitte; Martin, Ludovic; Hu, Weiguo; Galibert, Marie-Dominique; Misery, Laurent

    2014-12-01

    Merkel cell carcinoma is believed to be derived from Merkel cells after infection by Merkel cell polyomavirus (MCPyV) and other poorly understood events. Transcriptional profiling using cDNA microarrays was performed on cells from MCPy-negative and MCPy-positive Merkel cell carcinomas and isolated normal Merkel cells. This microarray revealed numerous significantly upregulated genes and some downregulated genes. The extensive list of genes that were identified in these experiments provides a large body of potentially valuable information of Merkel cell carcinoma carcinogenesis and could represent a source of potential targets for cancer therapy.

  12. Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks

    Science.gov (United States)

    Nishtala, Sneha; Neelamraju, Yaseswini; Janga, Sarath Chandra

    2016-05-01

    RNA-binding proteins (RBPs) are pivotal in orchestrating several steps in the metabolism of RNA in eukaryotes thereby controlling an extensive network of RBP-RNA interactions. Here, we employed CLIP (cross-linking immunoprecipitation)-seq datasets for 60 human RBPs and RIP-ChIP (RNP immunoprecipitation-microarray) data for 69 yeast RBPs to construct a network of genome-wide RBP- target RNA interactions for each RBP. We show in humans that majority (~78%) of the RBPs are strongly associated with their target transcripts at transcript level while ~95% of the studied RBPs were also found to be strongly associated with expression levels of target transcripts when protein expression levels of RBPs were employed. At transcript level, RBP - RNA interaction data for the yeast genome, exhibited a strong association for 63% of the RBPs, confirming the association to be conserved across large phylogenetic distances. Analysis to uncover the features contributing to these associations revealed the number of target transcripts and length of the selected protein-coding transcript of an RBP at the transcript level while intensity of the CLIP signal, number of RNA-Binding domains, location of the binding site on the transcript, to be significant at the protein level. Our analysis will contribute to improved modelling and prediction of post-transcriptional networks.

  13. Transcriptional regulation of cathelicidin genes in chicken bone marrow cells.

    Science.gov (United States)

    Lee, Sang In; Jang, Hyun June; Jeon, Mi-hyang; Lee, Mi Ock; Kim, Jeom Sun; Jeon, Ik-Soo; Byun, Sung June

    2016-04-01

    Cathelicidins form a family of vertebrate-specific immune molecules with an evolutionarily conserved gene structure. We analyzed the expression patterns of cathelicidin genes (CAMP, CATH3, and CATHB1) in chicken bone marrow cells (BMCs) and chicken embryonic fibroblasts (CEFs). We found that CAMP and CATHB1 were significantly up-regulated in BMCs, whereas the expression of CATH3 did not differ significantly between BMCs and CEFs. To study the mechanism underlying the up-regulation of cathelicidin genes in BMCs, we predicted the transcription factors (TFs) that bind to the 5'-flanking regions of cathelicidin genes. CEBPA, EBF1, HES1, MSX1, and ZIC3 were up-regulated in BMCs compared to CEFs. Subsequently, when a siRNA-mediated knockdown assay was performed for MSX1, the expression of CAMP and CATHB1 was decreased in BMCs. We also showed that the transcriptional activity of the CAMP promoter was decreased by mutation of the MSX1-binding sites present within the 5'-flanking region of CAMP. These results increase our understanding of the regulatory mechanisms controlling cathelicidin genes in BMCs.

  14. Phytochrome and retrograde signalling pathways converge to antagonistically regulate a light-induced transcriptional network.

    Science.gov (United States)

    Martín, Guiomar; Leivar, Pablo; Ludevid, Dolores; Tepperman, James M; Quail, Peter H; Monte, Elena

    2016-05-06

    Plastid-to-nucleus retrograde signals emitted by dysfunctional chloroplasts impact photomorphogenic development, but the molecular link between retrograde- and photosensory-receptor signalling has remained unclear. Here, we show that the phytochrome and retrograde signalling (RS) pathways converge antagonistically to regulate the expression of the nuclear-encoded transcription factor GLK1, a key regulator of a light-induced transcriptional network central to photomorphogenesis. GLK1 gene transcription is directly repressed by PHYTOCHROME-INTERACTING FACTOR (PIF)-class bHLH transcription factors in darkness, but light-activated phytochrome reverses this activity, thereby inducing expression. Conversely, we show that retrograde signals repress this induction by a mechanism independent of PIF mediation. Collectively, our data indicate that light at moderate levels acts through the plant's nuclear-localized sensory-photoreceptor system to induce appropriate photomorphogenic development, but at excessive levels, sensed through the separate plastid-localized RS system, acts to suppress such development, thus providing a mechanism for protection against photo-oxidative damage by minimizing the tissue exposure to deleterious radiation.

  15. Transcription profile analysis reveals that zygotic division results in uneven distribution of specific transcripts in apical/basal cells of tobacco.

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    Ligang Ma

    Full Text Available BACKGROUND: Asymmetric zygotic division in higher plants results in the formation of an apical cell and a basal cell. These two embryonic cells possess distinct morphologies and cell developmental fates. It has been proposed that unevenly distributed cell fate determinants and/or distinct cell transcript profiles may be the underlying reason for their distinct fates. However, neither of these hypotheses has convincing support due to technical limitations. METHODOLOGY/PRINCIPAL FINDINGS: Using laser-controlled microdissection, we isolated apical and basal cells and constructed cell type-specific cDNA libraries. Transcript profile analysis revealed difference in transcript composition. PCR and qPCR analysis confirmed that transcripts of selected embryogenesis-related genes were cell-type preferentially distributed. Some of the transcripts that existed in zygotes were found distinctly existed in apical or basal cells. The cell type specific de novo transcription was also found after zygotic cell division. CONCLUSIONS/SIGNIFICANCE: Thus, we found that the transcript diversity occurs between apical and basal cells. Asymmetric zygotic division results in the uneven distribution of some embryogenesis related transcripts in the two-celled proembryos, suggesting that a differential distribution of some specific transcripts in the apical or basal cells may involve in guiding the two cell types to different developmental destinies.

  16. A genomic approach to identify regulatory nodes in the transcriptional network of systemic acquired resistance in plants.

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2006-11-01

    Full Text Available Many biological processes are controlled by intricate networks of transcriptional regulators. With the development of microarray technology, transcriptional changes can be examined at the whole-genome level. However, such analysis often lacks information on the hierarchical relationship between components of a given system. Systemic acquired resistance (SAR is an inducible plant defense response involving a cascade of transcriptional events induced by salicylic acid through the transcription cofactor NPR1. To identify additional regulatory nodes in the SAR network, we performed microarray analysis on Arabidopsis plants expressing the NPR1-GR (glucocorticoid receptor fusion protein. Since nuclear translocation of NPR1-GR requires dexamethasone, we were able to control NPR1-dependent transcription and identify direct transcriptional targets of NPR1. We show that NPR1 directly upregulates the expression of eight WRKY transcription factor genes. This large family of 74 transcription factors has been implicated in various defense responses, but no specific WRKY factor has been placed in the SAR network. Identification of NPR1-regulated WRKY factors allowed us to perform in-depth genetic analysis on a small number of WRKY factors and test well-defined phenotypes of single and double mutants associated with NPR1. Among these WRKY factors we found both positive and negative regulators of SAR. This genomics-directed approach unambiguously positioned five WRKY factors in the complex transcriptional regulatory network of SAR. Our work not only discovered new transcription regulatory components in the signaling network of SAR but also demonstrated that functional studies of large gene families have to take into consideration sequence similarity as well as the expression patterns of the candidates.

  17. Mutation of senataxin alters disease-specific transcriptional networks in patients with ataxia with oculomotor apraxia type 2.

    Science.gov (United States)

    Fogel, Brent L; Cho, Ellen; Wahnich, Amanda; Gao, Fuying; Becherel, Olivier J; Wang, Xizhe; Fike, Francesca; Chen, Leslie; Criscuolo, Chiara; De Michele, Giuseppe; Filla, Alessandro; Collins, Abigail; Hahn, Angelika F; Gatti, Richard A; Konopka, Genevieve; Perlman, Susan; Lavin, Martin F; Geschwind, Daniel H; Coppola, Giovanni

    2014-09-15

    Senataxin, encoded by the SETX gene, contributes to multiple aspects of gene expression, including transcription and RNA processing. Mutations in SETX cause the recessive disorder ataxia with oculomotor apraxia type 2 (AOA2) and a dominant juvenile form of amyotrophic lateral sclerosis (ALS4). To assess the functional role of senataxin in disease, we examined differential gene expression in AOA2 patient fibroblasts, identifying a core set of genes showing altered expression by microarray and RNA-sequencing. To determine whether AOA2 and ALS4 mutations differentially affect gene expression, we overexpressed disease-specific SETX mutations in senataxin-haploinsufficient fibroblasts and observed changes in distinct sets of genes. This implicates mutation-specific alterations of senataxin function in disease pathogenesis and provides a novel example of allelic neurogenetic disorders with differing gene expression profiles. Weighted gene co-expression network analysis (WGCNA) demonstrated these senataxin-associated genes to be involved in both mutation-specific and shared functional gene networks. To assess this in vivo, we performed gene expression analysis on peripheral blood from members of 12 different AOA2 families and identified an AOA2-specific transcriptional signature. WGCNA identified two gene modules highly enriched for this transcriptional signature in the peripheral blood of all AOA2 patients studied. These modules were disease-specific and preserved in patient fibroblasts and in the cerebellum of Setx knockout mice demonstrating conservation across species and cell types, including neurons. These results identify novel genes and cellular pathways related to senataxin function in normal and disease states, and implicate alterations in gene expression as underlying the phenotypic differences between AOA2 and ALS4.

  18. Hybrid modeling of the crosstalk between signaling and transcriptional networks using ordinary differential equations and multi-valued logic.

    Science.gov (United States)

    Khan, Faiz M; Schmitz, Ulf; Nikolov, Svetoslav; Engelmann, David; Pützer, Brigitte M; Wolkenhauer, Olaf; Vera, Julio

    2014-01-01

    A decade of successful results indicates that systems biology is the appropriate approach to investigate the regulation of complex biochemical networks involving transcriptional and post-transcriptional regulations. It becomes mandatory when dealing with highly interconnected biochemical networks, composed of hundreds of compounds, or when networks are enriched in non-linear motifs like feedback and feedforward loops. An emerging dilemma is to conciliate models of massive networks and the adequate description of non-linear dynamics in a suitable modeling framework. Boolean networks are an ideal representation of massive networks that are humble in terms of computational complexity and data demand. However, they are inappropriate when dealing with nested feedback/feedforward loops, structural motifs common in biochemical networks. On the other hand, models of ordinary differential equations (ODEs) cope well with these loops, but they require enormous amounts of quantitative data for a full characterization of the model. Here we propose hybrid models, composed of ODE and logical sub-modules, as a strategy to handle large scale, non-linear biochemical networks that include transcriptional and post-transcriptional regulations. We illustrate the construction of this kind of models using as example a regulatory network centered on E2F1, a transcription factor involved in cancer. The hybrid modeling approach proposed is a good compromise between quantitative/qualitative accuracy and scala