Variation in the Type I Interferon Gene Cluster on 9P21 Influences Susceptibility to Asthma and Atopy
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$ Gene Symbol A B 3 C 4 D 9 E 10 F 11 G 12 H 13 I 14 J. K 17 L 18 M 19 N 20 O. P 22 R 26 S 27 T 30 U 32 V. W. X. Y. Z 33 A ® ® Gene Symbol Gene ID Antibody Monoclonal Antibody Polyclonal MaxPab Full-length Protein Partial-length Protein Antibody Pair KIt siRNA/Chimera Gene Symbol Gene ID Antibody Monoclonal Antibody Polyclonal MaxPab Full-length Protein Partial-length Protein Antibody Pair KIt siRNA/Chimera A1CF 29974 ● ● ADAMTS13 11093 ● ● ● ● ● A2M 2 ● ● ● ● ● ● ADAMTS20 80070 ● AACS 65985 ● ● ● ADAMTS5 11096 ● ● ● AANAT 15 ● ● ADAMTS8 11095 ● ● ● ● AATF 26574 ● ● ● ● ● ADAMTSL2 9719 ● AATK 9625 ● ● ● ● ADAMTSL4 54507 ● ● ABCA1 19 ● ● ● ● ● ADAR 103 ● ● ABCA5 23461 ● ● ADARB1 104 ● ● ● ● ABCA7 10347 ● ADARB2 105 ● ABCB9 23457 ● ● ● ● ● ADAT1 23536 ● ● ABCC4 10257 ● ● ● ● ADAT2 134637 ● ● ABCC5 10057 ● ● ● ● ● ADAT3 113179 ● ● ● ABCC8 6833 ● ● ● ● ADCY10 55811 ● ● ABCD2 225 ● ADD1 118 ● ● ● ● ● ● ABCD4 5826 ● ● ● ADD3 120 ● ● ● ABCG1 9619 ● ● ● ● ● ADH5 128 ● ● ● ● ● ● ABL1 25 ● ● ADIPOQ 9370 ● ● ● ● ● ABL2 27 ● ● ● ● ● ADK 132 ● ● ● ● ● ABO 28 ● ● ADM 133 ● ● ● ABP1 26 ● ● ● ● ● ADNP 23394 ● ● ● ● ABR 29 ● ● ● ● ● ADORA1 134 ● ● ACAA2 10449 ● ● ● ● ADORA2A 135 ● ● ● ● ● ● ● ACAN 176 ● ● ● ● ● ● ADORA2B 136 ● ● ACE 1636 ● ● ● ● ADRA1A 148 ● ● ● ● ACE2 59272 ● ● ADRA1B 147 ● ● ACER2 340485 ● ADRA2A 150 ● ● ACHE 43 ● ● ● ● ● ● ADRB1 153 ● ● ACIN1 22985 ● ● ● ADRB2 154 ● ● ● ● ● ACOX1 51 ● ● ● ● ● ADRB3 155 ● ● ● ● ACP5 54 ● ● ● ● ● ● ● ADRBK1 156 ● ● ● ● ACSF2 80221 ● ● ADRM1 11047 ● ● ● ● ACSF3 197322 ● ● AEBP1 165 ● ● ● ● ACSL4 2182 ● -
Cytokine Nomenclature
RayBiotech, Inc. The protein array pioneer company Cytokine Nomenclature Cytokine Name Official Full Name Genbank Related Names Symbol 4-1BB TNFRSF Tumor necrosis factor NP_001552 CD137, ILA, 4-1BB ligand receptor 9 receptor superfamily .2. member 9 6Ckine CCL21 6-Cysteine Chemokine NM_002989 Small-inducible cytokine A21, Beta chemokine exodus-2, Secondary lymphoid-tissue chemokine, SLC, SCYA21 ACE ACE Angiotensin-converting NP_000780 CD143, DCP, DCP1 enzyme .1. NP_690043 .1. ACE-2 ACE2 Angiotensin-converting NP_068576 ACE-related carboxypeptidase, enzyme 2 .1 Angiotensin-converting enzyme homolog ACTH ACTH Adrenocorticotropic NP_000930 POMC, Pro-opiomelanocortin, hormone .1. Corticotropin-lipotropin, NPP, NP_001030 Melanotropin gamma, Gamma- 333.1 MSH, Potential peptide, Corticotropin, Melanotropin alpha, Alpha-MSH, Corticotropin-like intermediary peptide, CLIP, Lipotropin beta, Beta-LPH, Lipotropin gamma, Gamma-LPH, Melanotropin beta, Beta-MSH, Beta-endorphin, Met-enkephalin ACTHR ACTHR Adrenocorticotropic NP_000520 Melanocortin receptor 2, MC2-R hormone receptor .1 Activin A INHBA Activin A NM_002192 Activin beta-A chain, Erythroid differentiation protein, EDF, INHBA Activin B INHBB Activin B NM_002193 Inhibin beta B chain, Activin beta-B chain Activin C INHBC Activin C NM005538 Inhibin, beta C Activin RIA ACVR1 Activin receptor type-1 NM_001105 Activin receptor type I, ACTR-I, Serine/threonine-protein kinase receptor R1, SKR1, Activin receptor-like kinase 2, ALK-2, TGF-B superfamily receptor type I, TSR-I, ACVRLK2 Activin RIB ACVR1B -
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. -
To Study Mutant P53 Gain of Function, Various Tumor-Derived P53 Mutants
Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science By Shama K Khokhar M.Sc., Bilaspur University, 2004 B.Sc., Bhopal University, 2002 2007 1 COPYRIGHT SHAMA K KHOKHAR 2007 2 WRIGHT STATE UNIVERSITY SCHOOL OF GRADUATE STUDIES Date of Defense: 12-03-07 I HEREBY RECOMMEND THAT THE THESIS PREPARED UNDER MY SUPERVISION BY SHAMA KHAN KHOKHAR ENTITLED Differential effects of mutant TAp63γ on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression BE ACCEPTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Master of Science Madhavi P. Kadakia, Ph.D. Thesis Director Daniel Organisciak , Ph.D. Department Chair Committee on Final Examination Madhavi P. Kadakia, Ph.D. Steven J. Berberich, Ph.D. Michael Leffak, Ph.D. Joseph F. Thomas, Jr., Ph.D. Dean, School of Graduate Studies 3 Abstract Khokhar, Shama K. M.S., Department of Biochemistry and Molecular Biology, Wright State University, 2007 Differential effect of TAp63γ mutants on transactivation of p53 and/or p63 responsive genes and their effects on global gene expression. p63, a member of the p53 gene family, known to play a role in development, has more recently also been implicated in cancer progression. Mice lacking p63 exhibit severe developmental defects such as limb truncations, abnormal skin, and absence of hair follicles, teeth, and mammary glands. Germline missense mutations of p63 have been shown to be responsible for several human developmental syndromes including SHFM, EEC and ADULT syndromes and are associated with anomalies in the development of organs of epithelial origin. -
Supplemental Materials ZNF281 Enhances Cardiac Reprogramming
Supplemental Materials ZNF281 enhances cardiac reprogramming by modulating cardiac and inflammatory gene expression Huanyu Zhou, Maria Gabriela Morales, Hisayuki Hashimoto, Matthew E. Dickson, Kunhua Song, Wenduo Ye, Min S. Kim, Hanspeter Niederstrasser, Zhaoning Wang, Beibei Chen, Bruce A. Posner, Rhonda Bassel-Duby and Eric N. Olson Supplemental Table 1; related to Figure 1. Supplemental Table 2; related to Figure 1. Supplemental Table 3; related to the “quantitative mRNA measurement” in Materials and Methods section. Supplemental Table 4; related to the “ChIP-seq, gene ontology and pathway analysis” and “RNA-seq” and gene ontology analysis” in Materials and Methods section. Supplemental Figure S1; related to Figure 1. Supplemental Figure S2; related to Figure 2. Supplemental Figure S3; related to Figure 3. Supplemental Figure S4; related to Figure 4. Supplemental Figure S5; related to Figure 6. Supplemental Table S1. Genes included in human retroviral ORF cDNA library. Gene Gene Gene Gene Gene Gene Gene Gene Symbol Symbol Symbol Symbol Symbol Symbol Symbol Symbol AATF BMP8A CEBPE CTNNB1 ESR2 GDF3 HOXA5 IL17D ADIPOQ BRPF1 CEBPG CUX1 ESRRA GDF6 HOXA6 IL17F ADNP BRPF3 CERS1 CX3CL1 ETS1 GIN1 HOXA7 IL18 AEBP1 BUD31 CERS2 CXCL10 ETS2 GLIS3 HOXB1 IL19 AFF4 C17ORF77 CERS4 CXCL11 ETV3 GMEB1 HOXB13 IL1A AHR C1QTNF4 CFL2 CXCL12 ETV7 GPBP1 HOXB5 IL1B AIMP1 C21ORF66 CHIA CXCL13 FAM3B GPER HOXB6 IL1F3 ALS2CR8 CBFA2T2 CIR1 CXCL14 FAM3D GPI HOXB7 IL1F5 ALX1 CBFA2T3 CITED1 CXCL16 FASLG GREM1 HOXB9 IL1F6 ARGFX CBFB CITED2 CXCL3 FBLN1 GREM2 HOXC4 IL1F7 -
Transcriptional Repression of IFN Regulatory Factor 7 by MYC Is Critical for Type I IFN Production in Human Plasmacytoid Dendrit
Transcriptional Repression of IFN Regulatory Factor 7 by MYC Is Critical for Type I IFN Production in Human Plasmacytoid Dendritic Cells This information is current as of September 28, 2021. Tae Whan Kim, Seunghee Hong, Yin Lin, Elise Murat, HyeMee Joo, Taeil Kim, Virginia Pascual and Yong-Jun Liu J Immunol 2016; 197:3348-3359; Prepublished online 14 September 2016; doi: 10.4049/jimmunol.1502385 Downloaded from http://www.jimmunol.org/content/197/8/3348 Supplementary http://www.jimmunol.org/content/suppl/2016/09/14/jimmunol.150238 http://www.jimmunol.org/ Material 5.DCSupplemental References This article cites 74 articles, 25 of which you can access for free at: http://www.jimmunol.org/content/197/8/3348.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 28, 2021 • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication *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 © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Transcriptional Repression of IFN Regulatory Factor 7 by MYC Is Critical for Type I IFN Production in Human Plasmacytoid Dendritic Cells Tae Whan Kim,*,1 Seunghee Hong,*,1 Yin Lin,* Elise Murat,* HyeMee Joo,* Taeil Kim,†,2 Virginia Pascual,* and Yong-Jun Liu*,† Type I IFNs are crucial mediators of human innate and adaptive immunity and are massively produced from plasmacytoid dendritic cells (pDCs). -
Secretome Screening Reveals Immunomodulating Functions Of
www.nature.com/scientificreports OPEN Secretome screening reveals immunomodulating functions of IFNα‑7, PAP and GDF‑7 on regulatory T‑cells Mei Ding1*, Rajneesh Malhotra2, Tomas Ottosson2, Magnus Lundqvist3, Aman Mebrahtu3, Johan Brengdahl1, Ulf Gehrmann2, Elisabeth Bäck4, Douglas Ross‑Thriepland5, Ida Isaksson6, Björn Magnusson1, Kris F. Sachsenmeier7, Hanna Tegel3, Sophia Hober3, Mathias Uhlén3, Lorenz M. Mayr5, Rick Davies5, Johan Rockberg3 & Lovisa Holmberg Schiavone1* Regulatory T cells (Tregs) are the key cells regulating peripheral autoreactive T lymphocytes. Tregs exert their function by suppressing efector T cells. Tregs have been shown to play essential roles in the control of a variety of physiological and pathological immune responses. However, Tregs are unstable and can lose the expression of FOXP3 and suppressive functions as a consequence of outer stimuli. Available literature suggests that secreted proteins regulate Treg functional states, such as diferentiation, proliferation and suppressive function. Identifcation of secreted proteins that afect Treg cell function are highly interesting for both therapeutic and diagnostic purposes in either hyperactive or immunosuppressed populations. Here, we report a phenotypic screening of a human secretome library in human Treg cells utilising a high throughput fow cytometry technology. Screening a library of 575 secreted proteins allowed us to identify proteins stabilising or destabilising the Treg phenotype as suggested by changes in expression of Treg marker proteins FOXP3 and/or CTLA4. Four proteins including GDF‑7, IL‑10, PAP and IFNα‑7 were identifed as positive regulators that increased FOXP3 and/or CTLA4 expression. PAP is a phosphatase. A catalytic‑dead version of the protein did not induce an increase in FOXP3 expression. -
Interferon-Α Therapy in Bcr-Abl-Negative Myeloproliferative Neoplasms
Leukemia (2008) 22, 1990–1998 & 2008 Macmillan Publishers Limited All rights reserved 0887-6924/08 $32.00 www.nature.com/leu SPOTLIGHT REVIEW Interferon-a therapy in bcr-abl-negative myeloproliferative neoplasms J-J Kiladjian1,2,3, C Chomienne4 and P Fenaux1 1Assistance PubliqueFHoˆpitaux de Paris, Hoˆpital Avicenne, Service d’He´matologie Clinique, Bobigny, France; 2Assistance PubliqueFHoˆpitaux de Paris, Hoˆpital Saint-Louis, Centre d’Investigation Clinique, Paris, France; 3Universite´ Paris 7, Denis Diderot, Paris, France and 4Assistance PubliqueFHoˆpitaux de Paris, Hoˆpital Saint-Louis, Unite´ de Biologie Cellulaire, Paris, France Interferon (IFN) was the first cytokine discovered 50 years ago, however, did not allow complete purity, and although leukocyte with a wide range of biological properties, including immuno- IFN consisted predominantly of IFN-a, small amounts of other modulatory, proapoptotic and antiangiogenic activities, that rapidly raised interest in its therapeutic use in malignancies. IFN species were also present. Later on, the cloning of IFN-receptor characterization was also pivotal in the discovery recombinant human IFN-a and -b in 1980 allowed the SPOTLIGHT of the JAK/STAT signaling pathway. Among the large IFN production of large amounts of IFN for characterization, family, mainly one of the type I IFN, IFN-a2, is used in therapy. biological activity studies and clinical trials.5–7 It is only 20 Many clinical trials have shown remarkable efficacy of IFN-a in years after their discovery that two IFN species, IFN-a and -b, bcr-abl-negative myeloproliferative neoplasms (MPNs), espe- could be purified satisfactorily using high-performance liquid cially polycythemia vera (PV), and essential thrombocythemia 8 (ET). -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
Recombinant Human IFN-Α6 Mammalian Cell-Expressed Human Interferon Alpha 6 (Alpha K) with HSA Cat
Recombinant human IFN-α6 Mammalian cell-expressed human interferon alpha 6 (alpha K) with HSA Cat. code: rcyc-hifna6 https://www.invivogen.com/human-ifna6 For research use only, not for diagnostic or therapeutic use Version 18I12-NJ PRODUCT INFORMATION BACKGROUND Contents Type I interferons (IFN) include the IFN-α family, IFN-β, IFN-ε, IFN-κ • 1 µg of lyophilized recombinant human IFN-α6 and IFN-ω. IFN-αs are important anti-viral cytokines that also play Note: This product is sterile filtered prior to lyophilization. anti-proliferative and immuno-modulatory functions. The human IFN-α • 1.5 ml endotoxin-free water family comprises 13 genes encoding 12 proteins, IFN-α13 being identical to IFN-α1. All IFN-αs bind to a common heterodimer receptor IFNAR1/ Storage and stability IFNAR2. The ternary complex signals through the Janus kinase (JAK) • Recombinant human IFN-α6 is shipped at room temperature. Upon and signal transducer and activator of transcription (STAT) signaling receipt it should be immediately stored at -20 °C. Lyophilized product is stable for 6 months at -20°C. pathway, inducing the formation of the ISGF3 transcriptional complex • Upon resuspension, prepare aliquots of recombinant human IFN-α6 and (STAT1/STAT2/IRF9). ISGF3 binds to IFN-stimulated response elements 2 store at -80 °C for 4 months. (ISRE) in the promoters of numerous IFN-stimulated genes (ISGs) . Note: Avoid repeated freeze-thaw cycles. Quality control IFN-α IFN-α • Purity: ≥ 95% (SDS-PAGE) Low affinity High affinity • Endotoxin: ≤ 1 EU/µg • The biological activity has been confirmed using HEK-Blue™ IFN-α/β IFNAR1 IFNAR2 cells (see validation data sheet available on our website). -
Type I Interferons in Anticancer Immunity
REVIEWS Type I interferons in anticancer immunity Laurence Zitvogel1–4*, Lorenzo Galluzzi1,5–8*, Oliver Kepp5–9, Mark J. Smyth10,11 and Guido Kroemer5–9,12 Abstract | Type I interferons (IFNs) are known for their key role in antiviral immune responses. In this Review, we discuss accumulating evidence indicating that type I IFNs produced by malignant cells or tumour-infiltrating dendritic cells also control the autocrine or paracrine circuits that underlie cancer immunosurveillance. Many conventional chemotherapeutics, targeted anticancer agents, immunological adjuvants and oncolytic 1Gustave Roussy Cancer Campus, F-94800 Villejuif, viruses are only fully efficient in the presence of intact type I IFN signalling. Moreover, the France. intratumoural expression levels of type I IFNs or of IFN-stimulated genes correlate with 2INSERM, U1015, F-94800 Villejuif, France. favourable disease outcome in several cohorts of patients with cancer. Finally, new 3Université Paris Sud/Paris XI, anticancer immunotherapies are being developed that are based on recombinant type I IFNs, Faculté de Médecine, F-94270 Le Kremlin Bicêtre, France. type I IFN-encoding vectors and type I IFN-expressing cells. 4Center of Clinical Investigations in Biotherapies of Cancer (CICBT) 507, F-94800 Villejuif, France. Type I interferons (IFNs) were first discovered more than Type I IFNs in cancer immunosurveillance 5Equipe 11 labellisée par la half a century ago as the factors underlying viral inter Type I IFNs are known to mediate antineoplastic effects Ligue Nationale contre le ference — that is, the ability of a primary viral infection against several malignancies, which is a clinically rel Cancer, Centre de Recherche 1 des Cordeliers, F-75006 Paris, to render cells resistant to a second distinct virus . -
Heatmaps - the Gene Expression Edition
Heatmaps - the gene expression edition Jeff Oliver 20 July, 2020 An application of heatmap visualization to investigate differential gene expression. Learning objectives 1. Manipulate data into a ‘tidy’ format 2. Visualize data in a heatmap 3. Become familiar with ggplot syntax for customizing plots Heatmaps for differential gene expression Heatmaps are a great way of displaying three-dimensional data in only two dimensions. But how can we easily translate tabular data into a format for heatmap plotting? By taking advantage of “data munging” and graphics packages, heatmaps are relatively easy to produce in R. Getting started We are going to start by isolating different types of information by imposing structure in our file managment. That is, we are going to put our input data in one folder and any output such as plots or analytical results in a different folder. We can use the dir.create to create these two folders: dir.create("data") dir.create("output") For this lesson, we will use a subset of data on a study of gene expression in cells infected with the influenza virus (doi: 10.4049/jimmunol.1501557). The study infected human plasmacytoid dendritic cells with the influenza virus, and compared gene expression in those cells to gene expression in uninfected cells. Thegoal was to see how the flu virus affected the function of these immune system cells. The data for this lesson is available at: http://tinyurl.com/flu-expression-data or https://jcoliver.github.io/ learn-r/data/GSE68849-expression.csv. Download this comma separated file and put it in the data folder.