The GATA Site-Dependent Hemogen Promoter Is Transcriptionally Regulated by GATA1 in Hematopoietic and Leukemia Cells

Total Page:16

File Type:pdf, Size:1020Kb

The GATA Site-Dependent Hemogen Promoter Is Transcriptionally Regulated by GATA1 in Hematopoietic and Leukemia Cells Leukemia (2006) 20, 417–425 & 2006 Nature Publishing Group All rights reserved 0887-6924/06 $30.00 www.nature.com/leu ORIGINAL ARTICLE The GATA site-dependent hemogen promoter is transcriptionally regulated by GATA1 in hematopoietic and leukemia cells LV Yang1,9, J Wan2,9,YGe3,4,,ZFu2, SY Kim5, Y Fujiwara6, JW Taub3,7, LH Matherly,3,4, J Eliason8 and L Li1,2 1Center for Molecular Medicine and Genetics, Wayne State University School of Medicine, Detroit, MI, USA; 2Department of Internal Medicine, Wayne State University School of Medicine, Detroit, MI, USA; 3Experimental and Clinical Therapeutics Program, Barbara Ann Karmanos Cancer Institute, Detroit, MI, USA; 4Department of Pharmacology, Wayne State University School of Medicine, Detroit, MI, USA; 5Cold Spring Harbor Laboratories, Cold Spring Harbor, NY, USA; 6Children’s Hospital, Harvard Medical School, Boston, MA, USA; 7Children’s Hospital of Michigan, Detroit, MI, USA and 8Asterand Inc., Detroit, MI, USA Hemgn (a gene symbol for hemogen in mouse, EDAG in human pancreas, tonsil, colon and peripheral blood mononuclear and RP59 in rat) encodes a nuclear protein that is highly cells.2 EDAG is highly expressed in acute myeloid leukemia expressed in hematopoietic tissues and acute leukemia. To characterize its regulatory mechanisms, we examined the (AML) and acute lymphoblastic leukemia (ALL) and has been activities of a Hemgn promoter containing 2975 bp of 50 flanking demonstrated to be involved in erythroleukemia differentiation, sequence and 196 bp of 50 untranslated region (50 UTR) survival and apoptosis and cell transformation of NIH3T3 sequence both in vitro and in vivo: this promoter is preferen- cells.4,5 ALL these studies suggest that overexpression of EDAG tially activated in a hematopoietic cell line, not in nonhemato- in acute leukemia may play an important role in leukemogensis. poietic cell lines, and is sufficient to drive the transcription of a More recently, assocaition of overexpression of EDAG and no lacZ transgene in hematopoietic tissues in transgenic mice. Mutagenesis analyses showed that the 50 UTR including two remission in de novo AML has been reported: this result suggests highly conserved GATA boxes is critical for the promoter that EDAG may play a modulator role in AML and could be a 6 activity. GATA1, not GATA2, binds to the GATA binding sites new target in the treatment of AML. and transactivates the Hemgn promoter in a dose-dependent A number of hematopoietic-specific transcription factors are manner. Furthermore, the expression of human hemogen found to regulate the molecular pathways of hematopoiesis (EDAG) transcripts were closely correlated with levels of through direct binding to regulatory elements of key hemato- GATA1 transcripts in primary acute myeloid leukemia speci- 7 mens. This study suggests that the Hemgn promoter contains poietic genes. For instance, GATA proteins bind to the critical regulatory elements for its transcription in hematopoie- consensus sequence WGATAR in the promoter regions of a 8 tic tissues and Hemgn is a direct target of GATA1 in leukemia variety of erythroid genes. Members of the GATA family are cells. generally categorized as hematopoietic GATA factors and Leukemia (2006) 20, 417–425. doi:10.1038/sj.leu.2404105; cardiovascular GATA factors.9 Among the former, GATA1 and published online 9 February 2006 GATA2 play critical roles in hematopoiesis, particularly Keywords: hemogen; EDAG; GATA1; promoter; AML; leukemia erythropoiesis, whereas GATA3 is primarily involved in T-cell development.10 To gain further insights into the regulatory mechanism(s) of Hemgn, we isolated and characterized a Hemgn promoter. In Introduction this report, we show that the Hemgn promoter exhibits hematopoietic-specific activities both in vitro and in vivo. Hemgn is highly expressed in the hematopoietic system.1–3 The Mutagenesis, gel shifting and chromatin immunoprecipitation developmental expression pattern of Hemgn marks its hemato- (ChIP) analyses were used to demonstrate the transcriptionally poietic ontogeny. In early embryogenesis, the expression of important roles of the GATA boxes and their binding protein, Hemgn is detected in blood islands of the yolk sac and in GATA1, in the Hemgn 50 untranslated region (50 UTR). Finally, primitive blood.1 In later development, the expression is we report that expression of GATA1 and EDAG appear to be sequentially localized in active hematopoietic sites, such as coregulated in primary AML cells. fetal liver and bone marrow.1,3 Among hematopoietic lineages, Hemgn is predominantly expressed in erythroid and megakaryo- cytic precursor cells; it is also expressed in hematopoietic Materials and methods stem cells and early progenitors.1,3 However, it is absent in 1,3 matured lymphocytes. Just like Hemgn, the human hemogen Hemgn promoter isolation and sequence analysis orthologue (EDAG) exhibits specific expression in human A BAC clones (# 567P14) containing the full-length Hemgn gene hemotopoietic tissues and cells, including adult bone marrow 1 was screened from a mouse BAC genomic library CITB-CJ7-B and fetal liver. However, no EDAG transcripts are detected in (Research Genetics, Catalogue # 96021) (for details, see adult liver, heart, brain, skeletal muscle, kidney, spleen, Supplementary Information). A Hemgn promoter spanning 3171 bp (positions À2975 to þ 196) was amplified with pfu Correspondence: Dr L Li, 421 E. Canfield Ave. #1107, Detroit, Turbo DNA polymerase (Stratagene, CA, USA) using the BAC as Michigan 48201, USA. a template. The Hemgn promoter was confirmed by DNA E-mail: [email protected] 9These authors contribute equally to the paper. sequencing. The sequence homology comparison of human and Received 20 November 2005; accepted 29 November 2005; mouse Hemgn genes was performed using VISTA (http:// published online 9 February 2006 dcode.org) (Figure 1b).11 The sequences of mouse and human Transcriptional control of the hemogen promoter by GATA1 LV Yang et al 418 Figure 1 Sequence analyses of mouse and human hemogen promoters. (a) Schematic diagram of exon and intron distribution of hemogen. Please note that 1 h and 1t refer to the first exons of hematopoietic and testicular isoforms, respectively. (b) VISTA plot of DNA sequence conservation between mouse and human hemogen. The homology analysis is set at 70% identity within a 20-bp window: the blue and yellow peaks indicate coding sequence and UTRs of the hemogen cDNA, respectively; the red and pink peaks indicate evolutionarily conserved sequence in the promoter and intronal regions, respectively. (c) The alignment of proximal promoters and the first exons of mouse (GenBank accession#: DQ204723) and human hemogen. The conserved nucleotides are marked with *. The TATA box is labeled in red color; GATA boxes in blue color; and the translation initiation codon ATG in green color. The GATA boxes are boxed, and the sites for AML-1, Evi-1 and Ets are indicated by lines (Please refer the html file on the web for the colored Figure 1). proximal promoters and the first exons were aligned using CMS, an acute myeloid leukemia cell line (established from a ClustalW (http://www2.ebi.ac.uk/clustalw). The MatInspector 2-year-old girl with acute megakaryocytic leukemia (AMkL))13 program (http://www.gene-regulation.com/) was used to identify was a gift from Dr A Fuse (National Institute of Infectious putative hematopoietic-specific transcription factor binding sites Diseases, Tokyo, Japan). The AMkL cell line, Meg-01, was in the sequence (Figure 1c). obtained from the American Type Culture Collection (Manassas, VA, USA).14 Single colonies of CMS cells with stably transfected pcDNA3-GATA115 were screened for GATA1 expression by real Cell culture, transfections, and reporter assays time RT–PCR (for details see Supplementary Information). 10T1/2 (a mouse fibroblast cell line), PAC1 (a rat smooth muscle cell line), COS-7 (a monkey kidney cell line), C2C12 (a mouse skeletal muscle cell line) and K562 cells (a human erythroleu- Construction of Hemgn promoter deletion and mutant kemia cell line) were co-transfected with indicated plasmids and constructs 200 ng of pRL-SV40 Renilla Luciferase reporter (as an internal Deletion mutants of the Hemgn promoter were cloned into the control). The culture condition and transfection conditions are luciferase reporter vector pXP1.16 The constructs were verified detailed in Supplementary Information. Cells were harvested by sequencing. The primers for amplifying the corresponding 24 h after transfection and luciferase activities were measured Hemgn promoter and its deletion mutants were: 0 using Dual-Luciferaset reporter assay system (Promega, Madi- pHemgnÀ2975 þ 196:5-CGC GGA TCC CAC ATC AGA GAC son, WI, USA). ACC TTG CC and 50-CCG CTC GAG GGT ATT GGC TTT GAC 0 Drosophila Mel-2 cells (D. Mel-2, a Schneider S2 insect cell TTC AC; pHemgnÀ831 þ 196:5-CGC GGA TCC TTG AAC TAG line) from Invitrogen (Carlsbad, CA, USA) were co-transfected GGT GGC TCT GG and 50-CCG CTC GAG GGT ATT GGC TTT 0 with 1 mg of the Hemgn-luciferase reporter gene construct GAC TTC AC; pHemgnÀ404 þ 196:5-CGC GGA TCC AAC AGC (pHemgn-2975 þ 196luc) and GATA1 (50–400 ng pPacGA- CTA CCT AGG AAG AG and 50-CCG CTC GAG GGT ATT GGC 12 0 TA1) using Fugenet 6 reagent (Roche Diagnostics Corpora- TTT GAC TTC AC; pHemgnÀ2975 þ 12:5-CGC GGA TCC CAC tion, IN, USA). Cells were harvested after 24 h for luciferase ATC AGA GAC ACC TTG CC and 50-CCG CTC GAG ACA CTG assays using the Single Luciferase Assay System (Promega). CAC AGG TGT GAG GG. Luciferase activities were normalized to total cell protein, The core GATA binding sequences in the plasmid measured by the Bio-Rad protein assay system. pHemgnÀ2975 þ 196luc construct were mutated to cATA, a Leukemia Transcriptional control of the hemogen promoter by GATA1 LV Yang et al 419 change reported to abolish GATA binding,17–19 using the Real time RT-PCR Quickchanget site-directed mutagenesis kit (Stratagene, La Total RNAs were extracted from mock-transfected, and GATA1 0 Jolla, CA, USA).
Recommended publications
  • Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis
    Hindawi Disease Markers Volume 2019, Article ID 3521746, 10 pages https://doi.org/10.1155/2019/3521746 Research Article Investigation of Key Genes and Pathways in Inhibition of Oxycodone on Vincristine-Induced Microglia Activation by Using Bioinformatics Analysis Wei Liu,1 Jishi Ye,2 and Hong Yan 1 1Department of Anesthesiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430014, China 2Department of Anesthesiology, Renmin Hospital of Wuhan University, Wuhan, 430060 Hubei, China Correspondence should be addressed to Hong Yan; [email protected] Received 2 November 2018; Accepted 31 December 2018; Published 10 February 2019 Academic Editor: Hubertus Himmerich Copyright © 2019 Wei Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Introduction. The neurobiological mechanisms underlying the chemotherapy-induced neuropathic pain are only partially understood. Among them, microglia activation was identified as the key component of neuropathic pain. The aim of this study was to identify differentially expressed genes (DEGs) and pathways associated with vincristine-induced neuropathic pain by using bioinformatics analysis and observe the effects of oxycodone on these DEG expressions in a vincristine-induced microglia activation model. Methods. Based on microarray profile GSE53897, we identified DEGs between vincristine-induced neuropathic pain rats and the control group. Using the ToppGene database, the prioritization DEGs were screened and performed by gene ontology (GO) and signaling pathway enrichment. A protein-protein interaction (PPI) network was used to explore the relationship among DEGs.
    [Show full text]
  • A Draft Map of the Human Proteome
    ARTICLE doi:10.1038/nature13302 A draft map of the human proteome Min-Sik Kim1,2, Sneha M. Pinto3, Derese Getnet1,4, Raja Sekhar Nirujogi3, Srikanth S. Manda3, Raghothama Chaerkady1,2, Anil K. Madugundu3, Dhanashree S. Kelkar3, Ruth Isserlin5, Shobhit Jain5, Joji K. Thomas3, Babylakshmi Muthusamy3, Pamela Leal-Rojas1,6, Praveen Kumar3, Nandini A. Sahasrabuddhe3, Lavanya Balakrishnan3, Jayshree Advani3, Bijesh George3, Santosh Renuse3, Lakshmi Dhevi N. Selvan3, Arun H. Patil3, Vishalakshi Nanjappa3, Aneesha Radhakrishnan3, Samarjeet Prasad1, Tejaswini Subbannayya3, Rajesh Raju3, Manish Kumar3, Sreelakshmi K. Sreenivasamurthy3, Arivusudar Marimuthu3, Gajanan J. Sathe3, Sandip Chavan3, Keshava K. Datta3, Yashwanth Subbannayya3, Apeksha Sahu3, Soujanya D. Yelamanchi3, Savita Jayaram3, Pavithra Rajagopalan3, Jyoti Sharma3, Krishna R. Murthy3, Nazia Syed3, Renu Goel3, Aafaque A. Khan3, Sartaj Ahmad3, Gourav Dey3, Keshav Mudgal7, Aditi Chatterjee3, Tai-Chung Huang1, Jun Zhong1, Xinyan Wu1,2, Patrick G. Shaw1, Donald Freed1, Muhammad S. Zahari2, Kanchan K. Mukherjee8, Subramanian Shankar9, Anita Mahadevan10,11, Henry Lam12, Christopher J. Mitchell1, Susarla Krishna Shankar10,11, Parthasarathy Satishchandra13, John T. Schroeder14, Ravi Sirdeshmukh3, Anirban Maitra15,16, Steven D. Leach1,17, Charles G. Drake16,18, Marc K. Halushka15, T. S. Keshava Prasad3, Ralph H. Hruban15,16, Candace L. Kerr19{, Gary D. Bader5, Christine A. Iacobuzio-Donahue15,16,17, Harsha Gowda3 & Akhilesh Pandey1,2,3,4,15,16,20 The availability of human genome sequence has transformed biomedical research over the past decade. However, an equiv- alent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry.
    [Show full text]
  • Atypical Chromosome Abnormalities in Acute Myeloid Leukemia Type M4
    Genetics and Molecular Biology, 30, 1, 6-9 (2007) Copyright by the Brazilian Society of Genetics. Printed in Brazil www.sbg.org.br Short Communication Atypical chromosome abnormalities in acute myeloid leukemia type M4 Agnes C. Fett-Conte1, Roseli Viscardi Estrela2, Cristina B. Vendrame-Goloni3, Andréa B. Carvalho-Salles1, Octávio Ricci-Júnior4 and Marileila Varella-Garcia5 1Departamento de Biologia Molecular, Faculdade de Medicina de São José do Rio Preto, São José do Rio Preto, SP, Brazil. 2Austa Hospital, São José do Rio Preto, SP, Brazil. 3Departamento de Biologia, Instituto de Biociências, Letras e Ciências Exatas, Universidade Estadual Paulista, São José do Rio Preto, SP, Brazil. 4Hemocentro, São José do Rio Preto, SP, Brazil. 5Comprehensive Cancer Center, University of Colorado, Denver, CO, USA. Abstract This study reports an adult AML-M4 patient with atypical chromosomal aberrations present in all dividing bone mar- row cell at diagnosis: t(1;8)(p32.1;q24.2), der(9)t(9;10)(q22;?), and ins(19;9)(p13.3;q22q34) that may have origi- nated transcripts with leukemogenic potential. Key words: acute myeloid leukemia, chromosomal abnormalities, chromosomal translocations. Received: February 10, 2006; Accepted: June 22, 2006. Acute non-lymphocytic or myelogenous leukemia (Mitelman Database of Chromosome Aberration in Cancer (ANLL or AML) represents a hematopoietic malignancy 2006). Karyotype is generally an important prognostic fac- characterized by abnormal cell proliferation and stalled dif- tor in AML, a favorable prognosis being associated with ferentiation leading to the accumulation of immature cells minor karyotypic changes, low frequency of abnormal in the marrow itself, in peripheral blood and eventually in bone marrow cells and changes specifically involving the other tissues.
    [Show full text]
  • Expression Profiling of Sexually Dimorphic Genes in the Japanese
    www.nature.com/scientificreports OPEN Expression profling of sexually dimorphic genes in the Japanese quail, Coturnix japonica Miki Okuno1,5, Shuntaro Miyamoto2,5, Takehiko Itoh1, Masahide Seki3, Yutaka Suzuki3, Shusei Mizushima2,4 & Asato Kuroiwa2,4* Research on avian sex determination has focused on the chicken. In this study, we established the utility of another widely used animal model, the Japanese quail (Coturnix japonica), for clarifying the molecular mechanisms underlying gonadal sex diferentiation. In particular, we performed comprehensive gene expression profling of embryonic gonads at three stages (HH27, HH31 and HH38) by mRNA-seq. We classifed the expression patterns of 4,815 genes into nine clusters according to the extent of change between stages. Cluster 2 (characterized by an initial increase and steady levels thereafter), including 495 and 310 genes expressed in males and females, respectively, contained fve key genes involved in gonadal sex diferentiation. A GO analysis showed that genes in this cluster are related to developmental processes including reproductive structure development and developmental processes involved in reproduction were signifcant, suggesting that expression profling is an efective approach to identify novel candidate genes. Based on RNA-seq data and in situ hybridization, the expression patterns and localization of most key genes for gonadal sex diferentiation corresponded well to those of the chicken. Our results support the efectiveness of the Japanese quail as a model for studies gonadal sex diferentiation in birds. In birds, males are homogametic (ZZ) and females are heterogametic (ZW). Te sex determination mechanism involving gene(s) on the sex chromosome is highly conserved among birds. In chickens, sex determination is thought to occur afer embryonic day (E) 4.5, corresponding to Hamburger and Hamilton stage1 24 (HH24).
    [Show full text]
  • Gene Duplication and Neofunctionalization: POLR3G and POLR3GL
    Downloaded from genome.cshlp.org on September 27, 2021 - Published by Cold Spring Harbor Laboratory Press Research Gene duplication and neofunctionalization: POLR3G and POLR3GL Marianne Renaud,1 Viviane Praz,1,2 Erwann Vieu,1,5 Laurence Florens,3 Michael P. Washburn,3,4 Philippe l’Hoˆte,1 and Nouria Hernandez1,6 1Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, 1015 Lausanne, Switzerland; 2Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland; 3Stowers Institute for Medical Research, Kansas City, Missouri 64110, USA; 4Department of Pathology and Laboratory Medicine, The University of Kansas Medical Center, Kansas City, Kansas 66160, USA RNA polymerase III (Pol III) occurs in two versions, one containing the POLR3G subunit and the other the closely related POLR3GL subunit. It is not clear whether these two Pol III forms have the same function, in particular whether they recognize the same target genes. We show that the POLR3G and POLR3GL genes arose from a DNA-based gene duplication, probably in a common ancestor of vertebrates. POLR3G- as well as POLR3GL-containing Pol III are present in cultured cell lines and in normal mouse liver, although the relative amounts of the two forms vary, with the POLR3G-containing Pol III relatively more abundant in dividing cells. Genome-wide chromatin immunoprecipitations followed by high-throughput sequencing (ChIP-seq) reveal that both forms of Pol III occupy the same target genes, in very constant proportions within one cell line, suggesting that the two forms of Pol III have a similar function with regard to specificity for target genes. In contrast, the POLR3G promoter—not the POLR3GL promoter—binds the transcription factor MYC, as do all other pro- moters of genes encoding Pol III subunits.
    [Show full text]
  • Iron Deficiency Modifies Gene Expression Variation Induced by Augmented Hypoxia Sensing
    HHS Public Access Author manuscript Author Manuscript Author ManuscriptBlood Cells Author Manuscript Mol Dis. Author Author Manuscript manuscript; available in PMC 2015 January 01. Published in final edited form as: Blood Cells Mol Dis. 2014 January ; 52(1): 35–45. doi:10.1016/j.bcmd.2013.07.016. Iron deficiency modifies gene expression variation induced by augmented hypoxia sensing Xu Zhang1, Wei Zhang2,3, Shwu-Fan Ma4, Galina Miasniakova5, Adelina Sergueeva6, Tatiana Ammosova7, Min Xu7, Sergei Nekhai7, Mehdi Nourai7, Michael S. Wade8,9, Josef T. Prchal10, Joe G. N. Garcia#8,9, Roberto F. Machado#8,9, and Victor R. Gordeuk#1 1Comprehensive Sickle Cell Center, Section of Hematology/Oncology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA 2Department of Pediatrics, University of Illinois at Chicago, Chicago, IL, USA 3Institute of Human Genetics, University of Illinois at Chicago, Chicago, IL, USA 4Section of Pulmonary/Critical Care, Department of Medicine, University of Chicago, Chicago, IL, USA 5Chuvash Republic Clinical Hospital 2, Cheboksary, Russian Federation, Howard University, Washington, DC 6Cheboksary Children's Hospital, Cheboksary, Russian Federation, Howard University, Washington, DC 7Center for Sickle Cell Disease, Howard University, Washington, DC 8Section of Pulmonary, Critical Care & Sleep Medicine, Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA 9Institute for Personalized Respiratory Medicine, University of Illinois at Chicago, Chicago, IL, USA 10Departments of Medicine, Pathology and Genetics, University of Utah and VAH © 2013 Elsevier Inc. All rights reserved. Correspondence: Victor R. Gordeuk, MD, Suite 172, Clinical Sciences Building, 820 South Wood St., Chicago, IL 60612-7236 Tel 312-996-5680, Fax 312-996-5984, [email protected].
    [Show full text]
  • Winners Sorted by Institute-Center
    FARE2020WINNERS Sorted By Institute Ji Chen Postdoctoral Fellow CC Neuroscience - General Toward a Wearable Pediatric Robotic Knee Exoskeleton for Real World Overground Gait Rehabilitation in Ambulatory Individuals Crouch gait, or excessive knee flexion, is a debilitating gait pathology in children with cerebral palsy (CP). Surgery, bracing and therapy provide only short term correction of crouch and more sustainable solutions remain a significant challenge in children with CP. One major hurdle is achieving the required dosage and intensity of gait training necessary to produce meaningful long term improvements in walking ability. Rather than replace lost or absent function, gait training in CP population aims to improve the participant’s baseline walking pattern by encouraging longer bouts of training and exercise, which is different than in those with paralysis. Wearable robotic exoskeletons, as a potential strategy, can assist individuals with CP to gradually regain knee extension over time and help maintain it for longer periods through intense task-specific gait training. We previously tested our initial prototype which produced significant improvement in knee extension comparable in magnitude to reported results from orthopedic surgery. Children continued to exert voluntary knee extensor muscle when walking with the exoskeleton which indicated the device was assisting but not controlling their gait. These positive initial results motivated us to design second prototype to expand the user population, and to enable its effective use outside of the laboratory environment. The current version has individualized control capability and device portability for home use as it implemented a multi-layered closed loop control system and a microcontroller based data acquisition system.
    [Show full text]
  • Supplemental Material.Pdf
    Akagi and Li et al SUPPLEMENTAL INFORMATION Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability Keiko Akagi, Jingfeng Li, Tatevik Broutian, Hesed Padilla-Nash, Weihong Xiao, Bo Jiang, James W. Rocco, Theodoros N. Teknos, Bhavna Kumar, Danny Wangsa, Dandan He, Thomas Ried, David E. Symer, Maura L. Gillison SUPPLEMENTAL METHODS PAGE NO. 3 SUPPLEMENTAL FIGURES Supplemental Fig. 1. Broad distribution of breakpoints and rearrangements mapped to the HPV genome in various cancer samples. 5 Supplemental Fig. 2. HPV E6 and E7 oncogene transcripts are expressed in diverse cancers. 7 Supplemental Fig. 3. Comparison of mutational spectra in HPV-positive vs. HPV-negative cancer samples. 8 Supplemental Fig. 4. Genomic copy number changes occur recurrently in diverse cancer samples. 9 Supplemental Fig. 5. Structural variation in various cancer samples. 10 Supplemental Fig. 6. FISH and SKY confirm HPV clusters. 12 Supplemental Fig. 7. Enrichment of hyper-amplification and structural variants around HPV integration sites. 13 Supplemental Fig. 8. Quantitative PCR confirms HPV-associated genomic amplifications. 14 Supplemental Fig. 9. Connectivity maps of additional HPV-associated genomic structural variants in HNSCC cell lines. 16 Supplemental Fig. 10. Gene amplification from HPV-mediated structural variation results in upregulation of FOXE1, C9ORF156 and PIM1 transcripts in UPCI:SCC090 cells. 17 Supplemental Fig. 11. Gene breakage at SLC47A2 in UM-SCC-104 cells. 19 1 Akagi and Li et al SUPPLEMENTAL TABLES Supplemental Table 1. Summary of WGS statistics for 12 cancer samples 20 Supplemental Table 2. Clonal single nucleotide polymorphisms found in HPV16 viral genomes in cancer samples 21 Supplemental Table 3.
    [Show full text]
  • A Pathogenic and Clonally Expanded B Cell Transcriptome in Active Multiple Sclerosis
    A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis Akshaya Ramesha,b,1, Ryan D. Schuberta,b,1, Ariele L. Greenfielda,b,2, Ravi Dandekara,b,2, Rita Loudermilka,b, Joseph J. Sabatino Jra,b, Matthew T. Koelzerc, Edwina B. Trana,b, Kanishka Koshala,b, Kicheol Kima,b, Anne-Katrin Pröbstela,b, Debarko Banerjia,b, University of California, San Francisco MS-EPIC Team3, Chu-Yueh Guoa,b, Ari J. Greena,b, Riley M. Bovea,b, Joseph L. DeRisid,e, Jeffrey M. Gelfanda,b, Bruce A. C. Creea,b, Scott S. Zamvila,b,f, Sergio E. Baranzinia,b, Stephen L. Hausera,b, and Michael R. Wilsona,b,4 aWeill Institute for Neurosciences, University of California, San Francisco, CA 94158; bDepartment of Neurology, University of California, San Francisco, CA 94158; cDepartment of Mathematics, University of California, Los Angeles, CA 90095; dChan Zuckerberg Biohub, San Francisco, CA 94158; eDepartment of Biochemistry and Biophysics, University of California, San Francisco, CA 94158; and fProgram in Immunology, University of California, San Francisco, CA 94143 Edited by Lawrence Steinman, Stanford University School of Medicine, Stanford, CA, and approved August 3, 2020 (received for review May 6, 2020) Central nervous system B cells have several potential roles in may not only shed light on disease pathogenesis but also po- multiple sclerosis (MS): secretors of proinflammatory cytokines tentially provide more disease-specific and safer therapeutic and chemokines, presenters of autoantigens to T cells, producers targets to guide development of the next-generation of B cell of pathogenic antibodies, and reservoirs for viruses that trigger therapeutics. demyelination.
    [Show full text]
  • PDF Hosted at the Radboud Repository of the Radboud University Nijmegen
    PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/100868 Please be advised that this information was generated on 2017-12-06 and may be subject to change. Deciphering cellular responses to pathogens using genomics data Iziah Edwin Sama Deciphering cellular responses to pathogens using genomics data This research was performed at the Centre for Molecular and Biomolecular Informatics (CMBI), Nijmegen Centre of Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. Funding: This work was supported by the VIRGO consortium, an Innovative Cluster approved by the Netherlands Genomics Initiative and partially funded by the Dutch Government (BSIK 03012), The Netherlands. ISBN 978-90-9027062-3 © 2012 Iziah Edwin Sama All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, by print or otherwise, without permission in writing from the author Front Cover Image: A metaphorical illustration of the complexity in a host cell (the field), wherein fundamental moieties like proteins interact with each other (the network) in response to various pathogenic stimuli triggering respective cellular responses (the sub-fields demarcated by different line colors). The background is a picture of an indoors multi-sports field .The network is a protein-protein interaction network (HsapiensPPI of chapter 3) in which nodes represent proteins and edges between nodes indicate physical association. (Concept by Iziah Edwin Sama) Cover design and lay-out: In Zicht Grafisch Ontwerp, Arnhem Printed by: Ipskamp Drukkers, Enschede II Deciphering cellular responses to pathogens using genomics data Proefschrift ter verkrijging van de graad van doctor aan de Radboud Universiteit Nijmegen op gezag van de rector magnificus prof.
    [Show full text]
  • Proteomic Characterization of Hemogen in Erythropoiesis
    Proteomic Characterization of Hemogen in Erythropoiesis Brinda Somasundaram This thesis is submitted to the Faculty of Graduate and Postdoctoral Studies in partial fulfillment of the requirements for a Master of Science degree in Cellular and Molecular Medicine. Department of Cellular and Molecular Medicine Faculty of Medicine University of Ottawa August 2nd, 2012 © Brinda Somasundaram, Ottawa, Canada 2012 ABSTRACT Hemogen (Hemgn) is reported as a tissue specific transcriptional regulator in testis as well as hematopoietic tissues. It is known that Hemgn positively regulates erythroid differentiation; however, the underlying molecular mechanism is not well understood. In the current study, using proteomic approach in combination with other molecular biology tools, we have attempted to decipher the role of Hemgn in differentiating Murine erythroblast leukemia (MEL) cells as a model system. Our study reveals that Hemgn predominantly interacts with transcriptional regulators, chromatin modifiers and histones. Furthermore, using Chromatin Immunoprecipitation and knockdown approach, we have demonstrated that Hemgn is recruited to the -globin locus, which is known to be activated during erythroid differentiation. Based on the results, we speculate that Hemgn acts as a tissue specific histone chaperone that regulates transcription during erythroid differentiation. TABLE OF CONTENTS List of Tables………………………………………………………………………. i List of Figures……………………………………………………………………… ii List of Abbreviations………………………………………………………………. iii Dedications and Acknowledgements.……………………………………………... v 1. INTRODUCTION…………………………………………………………….. 1 1.1. Chromatin Structure………………………………………………………... 2 1.2. Hematopoietic system – a brief overview………………………………….. 4 1.3. Erythropoiesis – from HSCs to being erythrocytes………………………... 6 1.4. Transcriptional regulation of erythropoiesis………………………………. 7 1.4.1. Hemogen – a novel transcription regulator………………………………... 8 1.4.2. GATA1 – master regulatory factor of erythropoiesis……………………... 9 1.4.3.
    [Show full text]
  • Table 2S List of the Probe Sets (Each of Them Corresponding to a Gene Or A
    Table 2s List of the probe sets (each of them corresponding to a gene or a gene family) resulting significantly modulated (see Table 1s) in DPTs following 3 hour Dex and whose increased/decreased modulation was above a chosen cut-off (for log increase > 0.75 and for log decrease < -0.5). In the Affymetrix platform each probe set is represented by an ID number (column 1) linked to a gene or gene family (columns 2 and 3). The modulation of the expression in the treated DPTs is reported as log in 2 basis (a 2 fold increase expression is reported as 1 and a 2 fold decrease expression is reported as –1). To allow comparison, the ID numbers of several data banks corresponding to the probe set ID are reported in columns 6- 14 and 19. Gene Ontology numbers and the pathway(s) in which the gene is involved are reported in columns 15-18. Affymetrix GeneChip Array Murine Genome U74Av2 Array Genome March 2005 (NCBI 34) Version column 1 column 2 column 3 column 4 column 5 column 6 column 7 column 8 column 9 column 10 column 11 column 12 column 13 column 14 Transcript Log2 Fold Representative Entrez RefSeq Transcript Probe Set ID Gene Title Gene Symbol ID (Array UniGene ID Ensembl SwissProt EC RefSeq Protein ID MGI Name Modulation Public ID Gene ID Design) ENSMUSG0 Q9CXH2 /// 95151_at RIKEN cDNA 2810052M02 gene 2810052M02Rik -2.8 5674136 AW061307 Mm.29475 67220 --- NP_075809.1 NM_023320 --- 0000015745 Q9JIY0 ENSMUSG0 P41133 /// 92614_at inhibitor of DNA binding 3 Id3 -2 5663577 M60523 Mm.110 15903 --- NP_032347.1 NM_008321 --- 0000007872 Q545W1 5690864_R
    [Show full text]