DOCSLIB.ORG

Exon Structure of the Nuclear Factor I DNA-Binding Domain from C

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text

Load more

Mammalian Genome 10, 390–396 (1999). Incorporating Mouse Genome © Springer-Verlag New York Inc. 1999 Exon structure of the Nuclear Factor I DNA-binding domain from C. elegans to mammals Colin F. Fletcher,1 Nancy A. Jenkins,1 Neal G. Copeland,1 Ali Z. Chaudhry,2 Richard M. Gronostajski2 1Mammalian Genetics Laboratory, ABL-Basic Research Program, NCI-Frederick Cancer Research and Development Center, Frederick, Maryland 21702, USA 2The Lerner Research Institute, Cleveland Clinic Foundation, 9500 Euclid Avenue, Dept. of Cancer Biology NB40, Cleveland, Ohio 44195 and Case Western Reserve University, Dept. of Biochemistry, Cleveland, Ohio, USA Received: 2 November 1998 / Accepted: 9 December 1998 Abstract. The Nuclear Factor I (NFI) family of DNA-binding Osada et al. 1996), hamster (Gil et al. 1988), pig (Meisterernst et proteins is essential for adenovirus DNA replication and the tran- al. 1989), chicken (Rupp et al. 1990; Kruse et al. 1991) and Xeno- scription of many cellular genes. Mammals have four genes en- pus (Roulet et al. 1995; Puzianowska-Kuznicka and Shi 1996) and coding NFI proteins, C. elegans has only a single NFI gene, and have been shown to be alternatively spliced, yielding as many as prokaryotes have none. To assess the relationship between mem- seven proteins from each gene (Kruse and Sippel 1994; Wen- bers of this unusually small family of transcription/replication fac- zelides et al. 1996). While the number of distinct transcripts from tors, we mapped the chromosomal locations of the four murine each gene is large, the same four NFI genes are present in all NFI genes and analyzed the exons encoding the DNA-binding vertebrate species examined to date and, unlike the Hox gene domains of the mouse, Amphioxus, and C. elegans NFI genes. The family (Carroll 1995), no extra-familial homologs have been de- four murine NFI genes are on Chrs 4 (Nfia and Nfib),8(Nfix), and tected. The apparent genetic simplicity of this gene family makes 10 (Nfic), suggesting early duplication of the genes and dispersal it a useful system to investigate gene-family expansion during throughout the genome. The DNA-binding domains of all four NFI metazoan evolution. genes are encoded by large (532 bp) exons with identical splice NFI proteins function by binding to duplex DNA containing acceptor and donor sites in each. In contrast, the C. elegans nfi-1 the consensus sequence TTGGC/AN5G/TCCAA (Gronostajski et gene has four phased introns interrupting this DNA-binding, do- al. 1985; Gronostajski 1986, 1987; Meisterernst et al. 1988) and main-encoding exon, and the last exon extends 213 bp past the modulating DNA replication and transcription. The DNA-binding splice site used in all four murine genes. In addition, the introns activity of NFI proteins resides in a highly homologous N-terminal present in C. elegans nfi-1 are missing from the NFI genes of DNA-binding domain (Mermod et al. 1989; Gounari et al. 1990; Amphioxus and all mammalian genomes examined. This analysis Novak et al. 1992), while the C-terminal regions of the proteins are of the exon structure of the C. elegans and murine NFI genes more divergent. Multiple C-terminal domains of each NFI gene indicates that the murine genes were probably generated by dupli- product are generated by alternative splicing (Kruse and Sippel cation of a C. elegans-like ancestral gene, but that significant 1994). The N-terminal DNA-binding domains of all NFI proteins changes have occurred in the genomic organization of either the C. elegans or murine NFI genes during evolution. appear to bind to the same DNA consensus sequence with appar- ently equal affinities (Meisterernst et al. 1988; Goyal et al. 1990) and are sufficient to stimulate adenovirus DNA replication in vitro (Mermod et al. 1989; Gounari et al. 1990). In contrast, activation Introduction of transcription requires both the DNA-binding domain and C- terminal transactivation domains (Mermod et al. 1989). The find- The Nuclear Factor I (NFI) gene family encodes a set of highly ing that NFI genes are differentially expressed during mouse de- conserved site-specific DNA-binding proteins required for both velopment and cellular differentiation suggests that NFI proteins adenovirus DNA replication (Nagata et al. 1983; Bosher et al. may play an important role in gene expression during development 1991; Armentero et al. 1994; Coenjaerts and van der Vliet 1994) (Kulkarni and Gronostajski 1996; Chaudhry et al. 1997). Since and the transcription of a variety of cellular and viral genes (Gold- NFI proteins differ in their ability to transactivate NFI-responsive berg et al. 1992; Cardinaux et al. 1994; Furlong et al. 1996; Krebs promoters, the precise mechanisms of stimulation of replication et al. 1996; Spitz et al. 1997). cDNAs encoding NFI proteins have and transcription may differ among the NFI proteins (Apt et al. been cloned from a number of species and define a set of four 1994; Krebs et al. 1996). paralogous genes (NFI-A, NFI-B, NFI-C, and NFI-X) that are Although four NFI genes are present in mammals, only a single conserved throughout vertebrate evolution (Rupp et al. 1990; NFI gene has been detected in the nematode C. elegans, and the Kruse et al. 1991). Transcripts from NFI genes have been cloned exon structure of the NFI gene in C. elegans differs considerably from human (Santoro et al. 1988; Apt et al. 1994; Qian et al. 1995; from those of some previously characterized mammalian NFI Kulkarni and Gronostajski 1996), mouse (Inoue et al. 1990; Nebl genes. Also, no NFI-like genes have been detected in any viral, and Cato 1995; Chaudhry et al. 1997), rat (Paonessa et al. 1988; fungal, bacterial, or archebacterial genomes sequenced to date. These data suggest either that the NFI gene family arose during The nucleotide sequence data reported in this paper have been submitted to metazoan evolution or was lost independently in a number of GenBank and have been assigned the accession numbers: AF059517 lineages. To examine the relationship between members of the NFI (xNFI-1), AF059518 (xNFI-2), AF059519 (xNFI-3), AF059520 (xNFI-4), gene family, we have mapped the locations of the NFI genes in the AF059521 (amphi-NFI), AF111263 (Nfia), AF111264 (Nfib), AF111265 mouse genome, characterized the exons encoding most of the (Nfic), AF111266 (Nfix). DNA-binding domain of the mouse genes, and compared the Correspondence to: R.M. Gronostajski, [email protected] DNA-binding domain-encoding exons of the C. elegans NFI gene C.F. Fletcher et al.: Structure and divergence of NFI genes 391 (nfi-1) with the mammalian and Amphioxus exons. Our studies in M. spretus DNA. The presence or absence of the 9.4-kb M. spretus- indicate that while the mammalian and C. elegans genes likely specific KpnI fragment was followed in backcross mice. The Nfic probe, an 32 share a common ancestral gene, significant changes have occurred 0.631-kb EcoRI fragment of human cDNA, was labeled with [␣ P] dCTP in exon organization during evolution of the NFI gene family. as above, and washing was to a final stringency of 0.8 × SSCP, 0.1% SDS, 65°C. Fragments of 7.4 and 3.5 kb were detected in BamHI-digested C57BL/6J DNA, and fragments of 7.4 and 4.9 kb were detected in M. Materials and methods spretus DNA. The presence or absence of the 4.9-kb M. spretus-specific BamHI fragment was followed in backcross mice. The Nfix probe, an 1.472-kb EcoRI fragment of human cDNA, was labeled as above, and Degenerate PCR and cloning of genomic and cDNA fragments. washing was to a final stringency of 0.8 × SSCP, 0.1% SDS, 65°C. Frag- Degenerate PCR to detect NFI genes was performed with either of two sets ments of 3.9 and 2.6 kb were detected in PvuII-digested C57BL/6J DNA, of primers: Deg 1 (5ЈTTCCGGATGARTTYCAYCITTYATYGARGC3Ј) and fragments of 6.0 and 2.6 kb were detected in M. spretus DNA. The and Deg 2 (5ЈAATCGATRTGRTGBGGCTGIAYRCAIAG3Ј) are primers presence or absence of the 6.0-kb M. spretus-specific PvuII fragment was used previously to clone NFI cDNAs from chicken (Rupp et al. 1990) and followed in backcross mice. The map locations of several other loci used human (Kulkarni and Gronostajski 1996) genomic DNA and do not am- to position the Nfi loci on our interspecific backcross have been previously plify the C. elegans nfi-1 gene (data not shown), while Deg 3 (5ЈTAY- described (Copeland and Jenkins 1991; Fletcher et al. 1996, 1997). Re- AMITGGTTYMAYCTICARG3Ј)andDeg4(5ЈCKYTCICCRTCIGTRC- combination distances were calculated as described by Green (1981), using TYTCS3Ј) were designed from the regions most highly conserved between the computer program MapManager. Gene order was determined by mini- C. elegans nfi-1 and vertebrate NFI genes and amplify NFI genes from both mizing the number of recombination events across the chromosome. C. elegans and vertebrates. Amplification was performed in 20- to 50-␮l reactions containing 10–300 ng of genomic DNA, 3 ␮M degenerate prim- ␮ ers, 200 M dNTPs, 50 mM Tris-HCl, pH 8.2, 1.5 mM MgCl2,50mM KCl, Results and 20 ␮g/ml BSA. Cycle times were 94° − 5Ј,35×(94°−1Ј, 50° − 2Ј, 72° − 3Ј), 72° − 7Ј for reactions used to clone PCR products. PCR products were repaired with T4 polymerase, cloned and sequenced. Amphioxus ge- Mapping of the mouse NFI genes. The Nfi loci are distributed in nomic DNA was a gift from Peter Holland (Univ. Reading, UK). the mouse genome and map to regions of conserved synteny with Genomic fragments containing the 2nd exons of the murine Nfia and their locations in the human genome (Fig.
Recommended publications
  • Identifying and Mapping Cell-Type-Specific Chromatin PNAS PLUS Programming of Gene Expression

    Identifying and Mapping Cell-Type-Specific Chromatin PNAS PLUS Programming of Gene Expression

    Identifying and mapping cell-type-specific chromatin PNAS PLUS programming of gene expression Troels T. Marstranda and John D. Storeya,b,1 aLewis-Sigler Institute for Integrative Genomics, and bDepartment of Molecular Biology, Princeton University, Princeton, NJ 08544 Edited by Wing Hung Wong, Stanford University, Stanford, CA, and approved January 2, 2014 (received for review July 2, 2013) A problem of substantial interest is to systematically map variation Relating DHS to gene-expression levels across multiple cell in chromatin structure to gene-expression regulation across con- types is challenging because the DHS represents a continuous ditions, environments, or differentiated cell types. We developed variable along the genome not bound to any specific region, and and applied a quantitative framework for determining the exis- the relationship between DHS and gene expression is largely tence, strength, and type of relationship between high-resolution uncharacterized. To exploit variation across cell types and test chromatin structure in terms of DNaseI hypersensitivity and genome- for cell-type-specific relationships between DHS and gene expres- wide gene-expression levels in 20 diverse human cell types. We sion, the measurement units must be placed on a common scale, show that ∼25% of genes show cell-type-specific expression ex- the continuous DHS measure associated to each gene in a well- plained by alterations in chromatin structure. We find that distal defined manner, and all measurements considered simultaneously. regions of chromatin structure (e.g., ±200 kb) capture more genes Moreover, the chromatin and gene-expression relationship may with this relationship than local regions (e.g., ±2.5 kb), yet the local only manifest in a single cell type, making standard measures of regions show a more pronounced effect.
  • The Activator Protein-1 Transcription Factor in Respiratory Epithelium Carcinogenesis

    The Activator Protein-1 Transcription Factor in Respiratory Epithelium Carcinogenesis

    Subject Review The Activator Protein-1 Transcription Factor in Respiratory Epithelium Carcinogenesis Michalis V. Karamouzis,1 Panagiotis A. Konstantinopoulos,1,2 and Athanasios G. Papavassiliou1 1Department of Biological Chemistry, Medical School, University of Athens, Athens, Greece and 2Division of Hematology-Oncology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts Abstract Much of the current anticancer research effort is focused on Respiratory epithelium cancers are the leading cause cell-surface receptors and their cognate upstream molecules of cancer-related death worldwide. The multistep natural because they provide the easiest route for drugs to affect history of carcinogenesis can be considered as a cellular behavior, whereas agents acting at the level of gradual accumulation of genetic and epigenetic transcription need to invade the nucleus. However, the aberrations, resulting in the deregulation of cellular therapeutic effect of surface receptor manipulation might be homeostasis. Growing evidence suggests that cross- considered less than specific because their actions are talk between membrane and nuclear receptor signaling modulated by complex interacting downstream signal trans- pathways along with the activator protein-1 (AP-1) duction pathways. A pivotal transcription factor during cascade and its cofactor network represent a pivotal respiratory epithelium carcinogenesis is activator protein-1 molecular circuitry participating directly or indirectly in (AP-1). AP-1–regulated genes include important modulators of respiratory epithelium carcinogenesis. The crucial role invasion and metastasis, proliferation, differentiation, and of AP-1 transcription factor renders it an appealing survival as well as genes associated with hypoxia and target of future nuclear-directed anticancer therapeutic angiogenesis (7). Nuclear-directed therapeutic strategies might and chemoprevention approaches.
  • A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    A Computational Approach for Defining a Signature of Β-Cell Golgi Stress in Diabetes Mellitus

    Page 1 of 781 Diabetes A Computational Approach for Defining a Signature of β-Cell Golgi Stress in Diabetes Mellitus Robert N. Bone1,6,7, Olufunmilola Oyebamiji2, Sayali Talware2, Sharmila Selvaraj2, Preethi Krishnan3,6, Farooq Syed1,6,7, Huanmei Wu2, Carmella Evans-Molina 1,3,4,5,6,7,8* Departments of 1Pediatrics, 3Medicine, 4Anatomy, Cell Biology & Physiology, 5Biochemistry & Molecular Biology, the 6Center for Diabetes & Metabolic Diseases, and the 7Herman B. Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN 46202; 2Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202; 8Roudebush VA Medical Center, Indianapolis, IN 46202. *Corresponding Author(s): Carmella Evans-Molina, MD, PhD ([email protected]) Indiana University School of Medicine, 635 Barnhill Drive, MS 2031A, Indianapolis, IN 46202, Telephone: (317) 274-4145, Fax (317) 274-4107 Running Title: Golgi Stress Response in Diabetes Word Count: 4358 Number of Figures: 6 Keywords: Golgi apparatus stress, Islets, β cell, Type 1 diabetes, Type 2 diabetes 1 Diabetes Publish Ahead of Print, published online August 20, 2020 Diabetes Page 2 of 781 ABSTRACT The Golgi apparatus (GA) is an important site of insulin processing and granule maturation, but whether GA organelle dysfunction and GA stress are present in the diabetic β-cell has not been tested. We utilized an informatics-based approach to develop a transcriptional signature of β-cell GA stress using existing RNA sequencing and microarray datasets generated using human islets from donors with diabetes and islets where type 1(T1D) and type 2 diabetes (T2D) had been modeled ex vivo. To narrow our results to GA-specific genes, we applied a filter set of 1,030 genes accepted as GA associated.
  • Transcriptional Control of Tissue-Resident Memory T Cell Generation

    Transcriptional Control of Tissue-Resident Memory T Cell Generation

    Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2019 © 2019 Filip Cvetkovski All rights reserved ABSTRACT Transcriptional control of tissue-resident memory T cell generation Filip Cvetkovski Tissue-resident memory T cells (TRM) are a non-circulating subset of memory that are maintained at sites of pathogen entry and mediate optimal protection against reinfection. Lung TRM can be generated in response to respiratory infection or vaccination, however, the molecular pathways involved in CD4+TRM establishment have not been defined. Here, we performed transcriptional profiling of influenza-specific lung CD4+TRM following influenza infection to identify pathways implicated in CD4+TRM generation and homeostasis. Lung CD4+TRM displayed a unique transcriptional profile distinct from spleen memory, including up-regulation of a gene network induced by the transcription factor IRF4, a known regulator of effector T cell differentiation. In addition, the gene expression profile of lung CD4+TRM was enriched in gene sets previously described in tissue-resident regulatory T cells. Up-regulation of immunomodulatory molecules such as CTLA-4, PD-1, and ICOS, suggested a potential regulatory role for CD4+TRM in tissues. Using loss-of-function genetic experiments in mice, we demonstrate that IRF4 is required for the generation of lung-localized pathogen-specific effector CD4+T cells during acute influenza infection. Influenza-specific IRF4−/− T cells failed to fully express CD44, and maintained high levels of CD62L compared to wild type, suggesting a defect in complete differentiation into lung-tropic effector T cells.
  • A Cell-Type-Specific Transcriptional Network Required for Estrogen Regulation of Cyclin D1 and Cell Cycle Progression in Breast Cancer

    A Cell-Type-Specific Transcriptional Network Required for Estrogen Regulation of Cyclin D1 and Cell Cycle Progression in Breast Cancer

    Downloaded from genesdev.cshlp.org on September 30, 2021 - Published by Cold Spring Harbor Laboratory Press A cell-type-specific transcriptional network required for estrogen regulation of cyclin D1 and cell cycle progression in breast cancer Jérôme Eeckhoute, Jason S. Carroll, Timothy R. Geistlinger, Maria I. Torres-Arzayus, and Myles Brown1 Division of Molecular and Cellular Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute and Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA Estrogen stimulates the proliferation of the most common type of human breast cancer that expresses estrogen receptor ␣ (ER␣) through the activation of the cyclin D1 (CCND1) oncogene. However, our knowledge of ER␣ transcriptional mechanisms remains limited. Hence, it is still elusive why ER␣ ectopically expressed in ER-negative breast cancer cells (BCC) is functional on ectopic reporter constructs but lacks activity on many endogenous target genes, including CCND1. Here, we show that estradiol (E2) stimulation of CCND1 expression in BCC depends on a novel cell-type-specific enhancer downstream from the CCND1 coding region, which is the primary ER␣ recruitment site in estrogen-responsive cells. The pioneer factor FoxA1 is specifically required for the active chromatin state of this enhancer and as such is crucial for both CCND1 expression and subsequent cell cycle progression. Interestingly, even in BCC, CCND1 levels and proliferation are tightly controlled by E2 through the establishment of a negative feedforward loop involving the induction of NFIC, a putative tumor suppressor capable of directly repressing CCND1 transcription. Taken together, our results reveal an estrogen-regulated combinatorial network including cell-specific cis- and trans-regulators of CCND1 expression where ER␣ collaborates with other transcription factors associated with the ER-positive breast cancer phenotype, including FoxA1 and NFIC.
  • Vascular Homeostasis and Inflammation in Health and Disease

    Vascular Homeostasis and Inflammation in Health and Disease

    International Journal of Molecular Sciences Review Vascular Homeostasis and Inflammation in Health and Disease—Lessons from Single Cell Technologies Olga Bondareva * and Bilal N. Sheikh * Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Philipp-Rosenthal-Str. 27, 04103 Leipzig, Germany * Correspondence: [email protected] (O.B.); [email protected] (B.N.S.); Tel.: +49-341-9722912 (B.N.S.) Received: 5 June 2020; Accepted: 30 June 2020; Published: 30 June 2020 Abstract: The vascular system is critical infrastructure that transports oxygen and nutrients around the body, and dynamically adapts its function to an array of environmental changes. To fulfil the demands of diverse organs, each with unique functions and requirements, the vascular system displays vast regional heterogeneity as well as specialized cell types. Our understanding of the heterogeneity of vascular cells and the molecular mechanisms that regulate their function is beginning to benefit greatly from the rapid development of single cell technologies. Recent studies have started to analyze and map vascular beds in a range of organs in healthy and diseased states at single cell resolution. The current review focuses on recent biological insights on the vascular system garnered from single cell analyses. We cover the themes of vascular heterogeneity, phenotypic plasticity of vascular cells in pathologies such as atherosclerosis and cardiovascular disease, as well as the contribution of defective microvasculature to the development of neurodegenerative disorders such as Alzheimer’s disease. Further adaptation of single cell technologies to study the vascular system will be pivotal in uncovering the mechanisms that drive the array of diseases underpinned by vascular dysfunction.
  • Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    Genome-Wide DNA Methylation Analysis of KRAS Mutant Cell Lines Ben Yi Tew1,5, Joel K

    www.nature.com/scientificreports OPEN Genome-wide DNA methylation analysis of KRAS mutant cell lines Ben Yi Tew1,5, Joel K. Durand2,5, Kirsten L. Bryant2, Tikvah K. Hayes2, Sen Peng3, Nhan L. Tran4, Gerald C. Gooden1, David N. Buckley1, Channing J. Der2, Albert S. Baldwin2 ✉ & Bodour Salhia1 ✉ Oncogenic RAS mutations are associated with DNA methylation changes that alter gene expression to drive cancer. Recent studies suggest that DNA methylation changes may be stochastic in nature, while other groups propose distinct signaling pathways responsible for aberrant methylation. Better understanding of DNA methylation events associated with oncogenic KRAS expression could enhance therapeutic approaches. Here we analyzed the basal CpG methylation of 11 KRAS-mutant and dependent pancreatic cancer cell lines and observed strikingly similar methylation patterns. KRAS knockdown resulted in unique methylation changes with limited overlap between each cell line. In KRAS-mutant Pa16C pancreatic cancer cells, while KRAS knockdown resulted in over 8,000 diferentially methylated (DM) CpGs, treatment with the ERK1/2-selective inhibitor SCH772984 showed less than 40 DM CpGs, suggesting that ERK is not a broadly active driver of KRAS-associated DNA methylation. KRAS G12V overexpression in an isogenic lung model reveals >50,600 DM CpGs compared to non-transformed controls. In lung and pancreatic cells, gene ontology analyses of DM promoters show an enrichment for genes involved in diferentiation and development. Taken all together, KRAS-mediated DNA methylation are stochastic and independent of canonical downstream efector signaling. These epigenetically altered genes associated with KRAS expression could represent potential therapeutic targets in KRAS-driven cancer. Activating KRAS mutations can be found in nearly 25 percent of all cancers1.
  • Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses

    Investigation of the Underlying Hub Genes and Molexular Pathogensis in Gastric Cancer by Integrated Bioinformatic Analyses

    bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Investigation of the underlying hub genes and molexular pathogensis in gastric cancer by integrated bioinformatic analyses Basavaraj Vastrad1, Chanabasayya Vastrad*2 1. Department of Biochemistry, Basaveshwar College of Pharmacy, Gadag, Karnataka 582103, India. 2. Biostatistics and Bioinformatics, Chanabasava Nilaya, Bharthinagar, Dharwad 580001, Karanataka, India. * Chanabasayya Vastrad [email protected] Ph: +919480073398 Chanabasava Nilaya, Bharthinagar, Dharwad 580001 , Karanataka, India bioRxiv preprint doi: https://doi.org/10.1101/2020.12.20.423656; this version posted December 22, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. Abstract The high mortality rate of gastric cancer (GC) is in part due to the absence of initial disclosure of its biomarkers. The recognition of important genes associated in GC is therefore recommended to advance clinical prognosis, diagnosis and and treatment outcomes. The current investigation used the microarray dataset GSE113255 RNA seq data from the Gene Expression Omnibus database to diagnose differentially expressed genes (DEGs). Pathway and gene ontology enrichment analyses were performed, and a proteinprotein interaction network, modules, target genes - miRNA regulatory network and target genes - TF regulatory network were constructed and analyzed. Finally, validation of hub genes was performed. The 1008 DEGs identified consisted of 505 up regulated genes and 503 down regulated genes.
  • Junb and GATA3 Transcription Factors Cytokine Expression Through Regulating CARMA1 Controls Th2 Cell-Specific

    Junb and GATA3 Transcription Factors Cytokine Expression Through Regulating CARMA1 Controls Th2 Cell-Specific

    CARMA1 Controls Th2 Cell-Specific Cytokine Expression through Regulating JunB and GATA3 Transcription Factors This information is current as Marzenna Blonska, Donghyun Joo, Patrick A. of September 27, 2021. Zweidler-McKay, Qingyu Zhao and Xin Lin J Immunol published online 27 February 2012 http://www.jimmunol.org/content/early/2012/02/26/jimmun ol.1102943 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2012/02/27/jimmunol.110294 Material 3.DC1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on September 27, 2021 *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2012 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. Published February 27, 2012, doi:10.4049/jimmunol.1102943 The Journal of Immunology CARMA1 Controls Th2 Cell-Specific Cytokine Expression through Regulating JunB and GATA3 Transcription Factors Marzenna Blonska,* Donghyun Joo,*,† Patrick A. Zweidler-McKay,‡ Qingyu Zhao,*,1 and Xin Lin*,† The scaffold protein CARMA1 is required for the TCR-induced lymphocyte activation.
  • Junb Differs from C-Jun in Its DNA- Binding and Dlmenzatlon Domains, and Represses C-Jun by Formation of Inactive Heterodimers

    Junb Differs from C-Jun in Its DNA- Binding and Dlmenzatlon Domains, and Represses C-Jun by Formation of Inactive Heterodimers

    Downloaded from genesdev.cshlp.org on October 3, 2021 - Published by Cold Spring Harbor Laboratory Press JunB differs from c-Jun in its DNA- binding and dlmenzatlon domains, and represses c-Jun by formation of inactive heterodimers Tiliang Deng and Michael Karin 1 Department of Pharmacology, Center for Molecular Genetics, University of California, San Diego, School of Medicine, La Jolla, California 92093-0636 USA JunB differs considerably from c-Jun in its ability to activate AP-l-responsive genes and induce oncogenic transformation. We demonstrate that the decreased ability of JunB to activate gene expression is the result of a small number of amino acid changes between its DNA-binding and dimerization motifs and the corresponding regions of c-Jun. These changes lead to a 10-fold decrease in the DNA-binding activity of Junk JunB can be converted into a c-Jun-like activator by substituting four amino acids in its DNA-binding and dimerization motifs with the corresponding c-Jun sequences. JunB can also attenuate trans-activation by c-Jun, an activity mediated by its leucine zipper. This ability depends on two glycine residues that decrease the stability of the JunB leucine zipper, resulting in decreased homodimerization and increased heterodimerization. These results illustrate how small changes in primary structure, including chemically conservative changes, can result in functional divergence of two highly related transcriptional regulators. [Key Words: JunB; c-Jun; DNA-binding/dimerization motifs; leucine zipper] Received October 16, 1992; revised version accepted December 29, 1992. Transcriptional control is commonly mediated by se- AP-1 was identified as a transcription factor required quence-specific DNA-binding proteins (Pabo and Saner for optimal activity of the human metallothionein IIA 1984; Johnson and McKnight 1989).
  • 1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor

    1714 Gene Comprehensive Cancer Panel Enriched for Clinically Actionable Genes with Additional Biologically Relevant Genes 400-500X Average Coverage on Tumor

    xO GENE PANEL 1714 gene comprehensive cancer panel enriched for clinically actionable genes with additional biologically relevant genes 400-500x average coverage on tumor Genes A-C Genes D-F Genes G-I Genes J-L AATK ATAD2B BTG1 CDH7 CREM DACH1 EPHA1 FES G6PC3 HGF IL18RAP JADE1 LMO1 ABCA1 ATF1 BTG2 CDK1 CRHR1 DACH2 EPHA2 FEV G6PD HIF1A IL1R1 JAK1 LMO2 ABCB1 ATM BTG3 CDK10 CRK DAXX EPHA3 FGF1 GAB1 HIF1AN IL1R2 JAK2 LMO7 ABCB11 ATR BTK CDK11A CRKL DBH EPHA4 FGF10 GAB2 HIST1H1E IL1RAP JAK3 LMTK2 ABCB4 ATRX BTRC CDK11B CRLF2 DCC EPHA5 FGF11 GABPA HIST1H3B IL20RA JARID2 LMTK3 ABCC1 AURKA BUB1 CDK12 CRTC1 DCUN1D1 EPHA6 FGF12 GALNT12 HIST1H4E IL20RB JAZF1 LPHN2 ABCC2 AURKB BUB1B CDK13 CRTC2 DCUN1D2 EPHA7 FGF13 GATA1 HLA-A IL21R JMJD1C LPHN3 ABCG1 AURKC BUB3 CDK14 CRTC3 DDB2 EPHA8 FGF14 GATA2 HLA-B IL22RA1 JMJD4 LPP ABCG2 AXIN1 C11orf30 CDK15 CSF1 DDIT3 EPHB1 FGF16 GATA3 HLF IL22RA2 JMJD6 LRP1B ABI1 AXIN2 CACNA1C CDK16 CSF1R DDR1 EPHB2 FGF17 GATA5 HLTF IL23R JMJD7 LRP5 ABL1 AXL CACNA1S CDK17 CSF2RA DDR2 EPHB3 FGF18 GATA6 HMGA1 IL2RA JMJD8 LRP6 ABL2 B2M CACNB2 CDK18 CSF2RB DDX3X EPHB4 FGF19 GDNF HMGA2 IL2RB JUN LRRK2 ACE BABAM1 CADM2 CDK19 CSF3R DDX5 EPHB6 FGF2 GFI1 HMGCR IL2RG JUNB LSM1 ACSL6 BACH1 CALR CDK2 CSK DDX6 EPOR FGF20 GFI1B HNF1A IL3 JUND LTK ACTA2 BACH2 CAMTA1 CDK20 CSNK1D DEK ERBB2 FGF21 GFRA4 HNF1B IL3RA JUP LYL1 ACTC1 BAG4 CAPRIN2 CDK3 CSNK1E DHFR ERBB3 FGF22 GGCX HNRNPA3 IL4R KAT2A LYN ACVR1 BAI3 CARD10 CDK4 CTCF DHH ERBB4 FGF23 GHR HOXA10 IL5RA KAT2B LZTR1 ACVR1B BAP1 CARD11 CDK5 CTCFL DIAPH1 ERCC1 FGF3 GID4 HOXA11 IL6R KAT5 ACVR2A
  • The Retinoblastoma Gene Family Members Prb and P107 Coactivate the AP-1-Dependent Mouse Tissue Factor Promoter in ®Broblasts

    The Retinoblastoma Gene Family Members Prb and P107 Coactivate the AP-1-Dependent Mouse Tissue Factor Promoter in ®Broblasts

    Oncogene (2000) 19, 3352 ± 3362 ã 2000 Macmillan Publishers Ltd All rights reserved 0950 ± 9232/00 $15.00 www.nature.com/onc The retinoblastoma gene family members pRB and p107 coactivate the AP-1-dependent mouse tissue factor promoter in ®broblasts Su-Ling Liu1, Arlymae Rand1, Robert J Kelm Jr,*,1 and Michael J Getz1,2 1Department of Biochemistry and Molecular Biology, Program in Tumor Biology, Mayo Clinic/Foundation, Rochester, Minnesota, MN 55905, USA Serum-stimulation of quiescent mouse ®broblasts results al., 1996), to maintenance of the placental labyrinth in transcriptional activation of tissue factor (TF), the during gestation (Erlich et al., 1999), and to tumor cellular initiator of blood coagulation. This requires the angiogenesis (Contrino et al., 1996). Tissue factor has rapid entry of c-Fos into speci®c AP-1 DNA-binding also been implicated as a determinant of metastatic complexes and can be strongly inhibited by the potential in melanoma cells (Mueller et al., 1992; adenovirus E1A 12S gene product. In this study, we Bromberg et al., 1995) and expression of TF in the utilized a panel of E1A mutants de®cient in cellular stromal compartment of breast carcinomas has been protein binding to analyse the molecular basis for E1A shown to correlate with progression to invasive inhibition of a minimal, c-Fos-dependent TF promoter/ cancer (Contrino et al., 1996; Vrana et al., 1996). reporter construct in mouse AKR-2B ®broblasts. Muta- Thus, it is important to understand how TF gene tions which impaired binding of the retinoblastoma tumor expression is regulated in both normal and neoplastic suppressor protein family members pRB, p107, and p130 cell types.