Supplemental Table 1 List of Genes Differentially Expressed In
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Educational Paper Ciliopathies
Eur J Pediatr (2012) 171:1285–1300 DOI 10.1007/s00431-011-1553-z REVIEW Educational paper Ciliopathies Carsten Bergmann Received: 11 June 2011 /Accepted: 3 August 2011 /Published online: 7 September 2011 # The Author(s) 2011. This article is published with open access at Springerlink.com Abstract Cilia are antenna-like organelles found on the (NPHP) . Ivemark syndrome . Meckel syndrome (MKS) . surface of most cells. They transduce molecular signals Joubert syndrome (JBTS) . Bardet–Biedl syndrome (BBS) . and facilitate interactions between cells and their Alstrom syndrome . Short-rib polydactyly syndromes . environment. Ciliary dysfunction has been shown to Jeune syndrome (ATD) . Ellis-van Crefeld syndrome (EVC) . underlie a broad range of overlapping, clinically and Sensenbrenner syndrome . Primary ciliary dyskinesia genetically heterogeneous phenotypes, collectively (Kartagener syndrome) . von Hippel-Lindau (VHL) . termed ciliopathies. Literally, all organs can be affected. Tuberous sclerosis (TSC) . Oligogenic inheritance . Modifier. Frequent cilia-related manifestations are (poly)cystic Mutational load kidney disease, retinal degeneration, situs inversus, cardiac defects, polydactyly, other skeletal abnormalities, and defects of the central and peripheral nervous Introduction system, occurring either isolated or as part of syn- dromes. Characterization of ciliopathies and the decisive Defective cellular organelles such as mitochondria, perox- role of primary cilia in signal transduction and cell isomes, and lysosomes are well-known -
Gene Expression Polarization
Transcriptional Profiling of the Human Monocyte-to-Macrophage Differentiation and Polarization: New Molecules and Patterns of Gene Expression This information is current as of September 27, 2021. Fernando O. Martinez, Siamon Gordon, Massimo Locati and Alberto Mantovani J Immunol 2006; 177:7303-7311; ; doi: 10.4049/jimmunol.177.10.7303 http://www.jimmunol.org/content/177/10/7303 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2006/11/03/177.10.7303.DC1 Material http://www.jimmunol.org/ References This article cites 61 articles, 22 of which you can access for free at: http://www.jimmunol.org/content/177/10/7303.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision by guest on September 27, 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 © 2006 by The American Association of Immunologists All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Transcriptional Profiling of the Human Monocyte-to-Macrophage Differentiation and Polarization: New Molecules and Patterns of Gene Expression1 Fernando O. -
Imm Catalog.Pdf
$ 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 ● -
Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse
Welcome to More Choice CD Marker Handbook For more information, please visit: Human bdbiosciences.com/eu/go/humancdmarkers Mouse bdbiosciences.com/eu/go/mousecdmarkers Human and Mouse CD Marker Handbook Human and Mouse CD Marker Key Markers - Human Key Markers - Mouse CD3 CD3 CD (cluster of differentiation) molecules are cell surface markers T Cell CD4 CD4 useful for the identification and characterization of leukocytes. The CD CD8 CD8 nomenclature was developed and is maintained through the HLDA (Human Leukocyte Differentiation Antigens) workshop started in 1982. CD45R/B220 CD19 CD19 The goal is to provide standardization of monoclonal antibodies to B Cell CD20 CD22 (B cell activation marker) human antigens across laboratories. To characterize or “workshop” the antibodies, multiple laboratories carry out blind analyses of antibodies. These results independently validate antibody specificity. CD11c CD11c Dendritic Cell CD123 CD123 While the CD nomenclature has been developed for use with human antigens, it is applied to corresponding mouse antigens as well as antigens from other species. However, the mouse and other species NK Cell CD56 CD335 (NKp46) antibodies are not tested by HLDA. Human CD markers were reviewed by the HLDA. New CD markers Stem Cell/ CD34 CD34 were established at the HLDA9 meeting held in Barcelona in 2010. For Precursor hematopoetic stem cell only hematopoetic stem cell only additional information and CD markers please visit www.hcdm.org. Macrophage/ CD14 CD11b/ Mac-1 Monocyte CD33 Ly-71 (F4/80) CD66b Granulocyte CD66b Gr-1/Ly6G Ly6C CD41 CD41 CD61 (Integrin b3) CD61 Platelet CD9 CD62 CD62P (activated platelets) CD235a CD235a Erythrocyte Ter-119 CD146 MECA-32 CD106 CD146 Endothelial Cell CD31 CD62E (activated endothelial cells) Epithelial Cell CD236 CD326 (EPCAM1) For Research Use Only. -
The Title of the Article
Mechanism-Anchored Profiling Derived from Epigenetic Networks Predicts Outcome in Acute Lymphoblastic Leukemia Xinan Yang, PhD1, Yong Huang, MD1, James L Chen, MD1, Jianming Xie, MSc2, Xiao Sun, PhD2, Yves A Lussier, MD1,3,4§ 1Center for Biomedical Informatics and Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637 USA 2State Key Laboratory of Bioelectronics, Southeast University, 210096 Nanjing, P.R.China 3The University of Chicago Cancer Research Center, and The Ludwig Center for Metastasis Research, The University of Chicago, Chicago, IL 60637 USA 4The Institute for Genomics and Systems Biology, and the Computational Institute, The University of Chicago, Chicago, IL 60637 USA §Corresponding author Email addresses: XY: [email protected] YH: [email protected] JC: [email protected] JX: [email protected] XS: [email protected] YL: [email protected] - 1 - Abstract Background Current outcome predictors based on “molecular profiling” rely on gene lists selected without consideration for their molecular mechanisms. This study was designed to demonstrate that we could learn about genes related to a specific mechanism and further use this knowledge to predict outcome in patients – a paradigm shift towards accurate “mechanism-anchored profiling”. We propose a novel algorithm, PGnet, which predicts a tripartite mechanism-anchored network associated to epigenetic regulation consisting of phenotypes, genes and mechanisms. Genes termed as GEMs in this network meet all of the following criteria: (i) they are co-expressed with genes known to be involved in the biological mechanism of interest, (ii) they are also differentially expressed between distinct phenotypes relevant to the study, and (iii) as a biomodule, genes correlate with both the mechanism and the phenotype. -
Unraveling the Genetics of Joubert and Meckel-Gruber Syndromes
Journal of Pediatric Genetics 3 (2014) 65–78 65 DOI 10.3233/PGE-14090 IOS Press Unraveling the genetics of Joubert and Meckel-Gruber syndromes Katarzyna Szymanska, Verity L. Hartill and Colin A. Johnson∗ Department of Ophthalmology and Neuroscience, University of Leeds, Leeds, UK Received 27 May 2014 Revised 11 July 2014 Accepted 14 July 2014 Abstract. Joubert syndrome (JBTS) and Meckel-Gruber syndrome (MKS) are recessive neurodevelopmental conditions caused by mutations in proteins that are structural or functional components of the primary cilium. In this review, we provide an overview of their clinical diagnosis, management and molecular genetics. Both have variable phenotypes, extreme genetic heterogeneity, and display allelism both with each other and other ciliopathies. Recent advances in genetic technology have significantly improved diagnosis and clinical management of ciliopathy patients, with the delineation of some general genotype-phenotype correlations. We highlight those that are most relevant for clinical practice, including the correlation between TMEM67 mutations and the JBTS variant phenotype of COACH syndrome. The subcellular localization of the known MKS and JBTS proteins is now well-described, and we discuss some of the contemporary ideas about ciliopathy disease pathogenesis. Most JBTS and MKS proteins localize to a discrete ciliary compartment called the transition zone, and act as structural components of the so-called “ciliary gate” to regulate the ciliary trafficking of cargo proteins or lipids. Cargo proteins include enzymes and transmembrane proteins that mediate intracellular signaling. The disruption of transition zone function may contribute to the ciliopathy phenotype by altering the composition of the ciliary membrane or axoneme, with impacts on essential developmental signaling including the Wnt and Shh pathways as well as the regulation of secondary messengers such as inositol-1,4,5-trisphosphate (InsP3) and cyclic adenosine monophosphate (cAMP). -
Identification and Diagnostic Performance of a Small RNA Within the PCA3 and BMCC1 Gene Locus That Potentially Targets Mrna
Published OnlineFirst November 12, 2014; DOI: 10.1158/1055-9965.EPI-14-0377 Research Article Cancer Epidemiology, Biomarkers Identification and Diagnostic Performance of a & Prevention Small RNA within the PCA3 and BMCC1 Gene Locus That Potentially Targets mRNA Ross M. Drayton1, Ishtiaq Rehman1, Raymond Clarke2, Zhongming Zhao3,4, Karl Pang1, Saiful Miah1, Robert Stoehr5, Arndt Hartmann5, Sheila Blizard1, Martin Lavin2, Helen E. Bryant1, Elena S. Martens-Uzunova6, Guido Jenster6, Freddie C. Hamdy7, Robert A. Gardiner2, and James W.F. Catto1 Abstract Background: PCA3 is a long noncoding RNA (lncRNA) with malignant prostatic tissues, exfoliated urinary cells from men unknown function, upregulated in prostate cancer. LncRNAs may with prostate cancer (13–273 fold change; t test P < 0.003), and be processed into smaller active species. We hypothesized this for closely correlated to PCA3 expression (r ¼ 0.84–0.93; P < 0.001). PCA3. Urinary PCA3-shRNA2 (C-index, 0.75–0.81) and PCA3 (C-index, Methods: We computed feasible RNA hairpins within the 0.78) could predict the presence of cancer in most men. PCA3- BMCC1 gene (encompassing PCA3) and searched a prostate shRNA2 knockup altered the expression of predicted target transcriptome for these. We measured expression using qRT- mRNAs, including COPS2, SOX11, WDR48, TEAD1, and Noggin. PCR in three cohorts of prostate cancer tissues (n ¼ 60), PCA3-shRNA2 expression was negatively correlated with COPS2 exfoliated urinary cells (n ¼ 484 with cancer and n ¼ 166 in patient samples (r ¼0.32; P < 0.001). controls), and in cell lines (n ¼ 22). We used in silico predictions Conclusion: We identified a short RNA within PCA3, whose and RNA knockup to identify potential mRNA targets of short expression is correlated to PCA3, which may target mRNAs transcribed RNAs. -
KLF2 Induced
UvA-DARE (Digital Academic Repository) The transcription factor KLF2 in vascular biology Boon, R.A. Publication date 2008 Link to publication Citation for published version (APA): Boon, R. A. (2008). The transcription factor KLF2 in vascular biology. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:23 Sep 2021 Supplementary data: Genes induced by KLF2 Dekker et al. LocusLink Accession Gene Sequence Description Fold p-value ID number symbol change (FDR) 6654 AK022099 SOS1 cDNA FLJ12037 fis, clone HEMBB1001921. 100.00 5.9E-09 56999 AF086069 ADAMTS9 full length insert cDNA clone YZ35C05. 100.00 1.2E-09 6672 AF085934 SP100 full length insert cDNA clone YR57D07. 100.00 6.7E-13 9031 AF132602 BAZ1B Williams Syndrome critical region WS25 mRNA, partial sequence. -
A Genome-Wide Association Study Lystra P
Hayden et al. Respiratory Research (2018) 19:209 https://doi.org/10.1186/s12931-018-0890-0 RESEARCH Open Access Childhood asthma is associated with COPD and known asthma variants in COPDGene: a genome-wide association study Lystra P. Hayden1,2* , Michael H. Cho2,3, Benjamin A. Raby1,2,3, Terri H. Beaty4, Edwin K. Silverman2,3, Craig P. Hersh2,3 and on behalf of the COPDGene Investigators Abstract Background: Childhood asthma is strongly influenced by genetics and is a risk factor for reduced lung function and chronic obstructive pulmonary disease (COPD) in adults. This study investigates self-reported childhood asthma in adult smokers from the COPDGene Study. We hypothesize that childhood asthma is associated with decreased lung function, increased risk for COPD, and that a genome-wide association study (GWAS) will show association with established asthma variants. Methods: We evaluated current and former smokers ages 45–80 of non-Hispanic white (NHW) or African American (AA) race. Childhood asthma was defined by self-report of asthma, diagnosed by a medical professional, with onset at < 16 years or during childhood. Subjects with a history of childhood asthma were compared to those who never had asthma based on lung function, development of COPD, and genetic variation. GWAS was performed in NHW and AA populations, and combined in meta-analysis. Two sets of established asthma SNPs from published literature were examined for association with childhood asthma. Results: Among 10,199 adult smokers, 730 (7%) reported childhood asthma and 7493 (73%) reported no history of asthma. Childhood asthmatics had reduced lung function and increased risk for COPD (OR 3.42, 95% CI 2.81–4.18). -
Downloaded from GEO
bioRxiv preprint doi: https://doi.org/10.1101/2020.08.17.252007; this version posted November 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Oxylipin metabolism is controlled by mitochondrial b-oxidation during bacterial inflammation. Mariya Misheva1, Konstantinos Kotzamanis1*, Luke C Davies1*, Victoria J Tyrrell1, Patricia R S Rodrigues1, Gloria A Benavides2, Christine Hinz1, Robert C Murphy3, Paul Kennedy4, Philip R Taylor1,5, Marcela Rosas1, Simon A Jones1, Sumukh Deshpande1, Robert Andrews1, Magdalena A Czubala1, Mark Gurney1, Maceler Aldrovandi1, Sven W Meckelmann1, Peter Ghazal1, Victor Darley-Usmar2, Daniel White1, and Valerie B O’Donnell1 1Systems Immunity Research Institute and Division of Infection and Immunity, and School of Medicine, Cardiff University, UK, 2Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35294, USA, 3Department of Pharmacology, University of Colorado Denver, Aurora, CO 80045, USA, 4Cayman Chemical 1180 E Ellsworth Rd, Ann Arbor, MI 48108, United States, 5UK Dementia Research Institute at Cardiff, Cardiff University, UK Address correspondence: Valerie O’Donnell, [email protected] or Daniel White, [email protected], Systems Immunity Research Institute, Cardiff University *Both authors contributed equally to the study 1 bioRxiv preprint doi: https://doi.org/10.1101/2020.08.17.252007; this version posted November 3, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Environmental Influences on Endothelial Gene Expression
ENDOTHELIAL CELL GENE EXPRESSION John Matthew Jeff Herbert Supervisors: Prof. Roy Bicknell and Dr. Victoria Heath PhD thesis University of Birmingham August 2012 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. ABSTRACT Tumour angiogenesis is a vital process in the pathology of tumour development and metastasis. Targeting markers of tumour endothelium provide a means of targeted destruction of a tumours oxygen and nutrient supply via destruction of tumour vasculature, which in turn ultimately leads to beneficial consequences to patients. Although current anti -angiogenic and vascular targeting strategies help patients, more potently in combination with chemo therapy, there is still a need for more tumour endothelial marker discoveries as current treatments have cardiovascular and other side effects. For the first time, the analyses of in-vivo biotinylation of an embryonic system is performed to obtain putative vascular targets. Also for the first time, deep sequencing is applied to freshly isolated tumour and normal endothelial cells from lung, colon and bladder tissues for the identification of pan-vascular-targets. Integration of the proteomic, deep sequencing, public cDNA libraries and microarrays, delivers 5,892 putative vascular targets to the science community.