Mouse Tmem150a Knockout Project (CRISPR/Cas9)
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Antibodies Products
Chapter 2 : Gentaur Products List • Human Signal peptidase complex catalytic subunit • Human Sjoegren syndrome nuclear autoantigen 1 SSNA1 • Human Small proline rich protein 2A SPRR2A ELISA kit SEC11A SEC11A ELISA kit SpeciesHuman ELISA kit SpeciesHuman SpeciesHuman • Human Signal peptidase complex catalytic subunit • Human Sjoegren syndrome scleroderma autoantigen 1 • Human Small proline rich protein 2B SPRR2B ELISA kit SEC11C SEC11C ELISA kit SpeciesHuman SSSCA1 ELISA kit SpeciesHuman SpeciesHuman • Human Signal peptidase complex subunit 1 SPCS1 ELISA • Human Ski oncogene SKI ELISA kit SpeciesHuman • Human Small proline rich protein 2D SPRR2D ELISA kit kit SpeciesHuman • Human Ski like protein SKIL ELISA kit SpeciesHuman SpeciesHuman • Human Signal peptidase complex subunit 2 SPCS2 ELISA • Human Skin specific protein 32 C1orf68 ELISA kit • Human Small proline rich protein 2E SPRR2E ELISA kit kit SpeciesHuman SpeciesHuman SpeciesHuman • Human Signal peptidase complex subunit 3 SPCS3 ELISA • Human SLAIN motif containing protein 1 SLAIN1 ELISA kit • Human Small proline rich protein 2F SPRR2F ELISA kit kit SpeciesHuman SpeciesHuman SpeciesHuman • Human Signal peptide CUB and EGF like domain • Human SLAIN motif containing protein 2 SLAIN2 ELISA kit • Human Small proline rich protein 2G SPRR2G ELISA kit containing protein 2 SCUBE2 ELISA kit SpeciesHuman SpeciesHuman SpeciesHuman • Human Signal peptide CUB and EGF like domain • Human SLAM family member 5 CD84 ELISA kit • Human Small proline rich protein 3 SPRR3 ELISA kit containing protein -
Characterisation of Isomirs in Stem Cells
Characterisation of isomiRs in stem cells Geok Chin Tan Institute of Reproductive and Developmental Biology Department of Surgery and Cancer Faculty of Medicine Imperial College London Thesis submitted to Imperial College London for the degree of Doctor of Philosophy 1 Statement of Originality All experiments included in this thesis were performed by me unless otherwise stated in the text. 2 Copyright Statement ‘The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work’ 3 Acknowledgements I would like to thank my supervisor Dr Nicholas Dibb for giving me the opportunity to work in his lab and for all of his guidance and support throughout my PhD, without which this project would not have been possible. I am also very grateful to Dr Wei Cui for teaching me the technique of stem cell culture, her comments on my project related to stem cells and as a wonderful co-supervisor. I would like to also thank Professor Malcolm Parker for his supports and advise on academic and non-academic related subjects. Many thanks to Elcie Chan for the generation of all the stem cell libraries which forms the platform for my project. My sincere thanks also to Gunter Meister for supplying the Argonaute antibodies, Leandro Castellano for the help in the design of RNA sponges, Laki Buluwela for the pTRIPz lentiviral vector and last but not least Alywn Dart from Charlotte Bevan group for the prostate cancer cell lines. -
Supplemental Table 1A. Differential Gene Expression Profile of Adehcd40l and Adehnull Treated Cells Vs Untreated Cells
Supplemental Table 1a. Differential Gene Expression Profile of AdEHCD40L and AdEHNull treated cells vs Untreated Cells Fold change Regulation Fold change Regulation ([AdEHCD40L] vs ([AdEHCD40L] ([AdEHNull] vs ([AdEHNull] vs Probe Set ID [Untreated]) vs [Untreated]) [Untreated]) [Untreated]) Gene Symbol Gene Title RefSeq Transcript ID NM_001039468 /// NM_001039469 /// NM_004954 /// 203942_s_at 2.02 down 1.00 down MARK2 MAP/microtubule affinity-regulating kinase 2 NM_017490 217985_s_at 2.09 down 1.00 down BAZ1A fibroblastbromodomain growth adjacent factor receptorto zinc finger 2 (bacteria-expressed domain, 1A kinase, keratinocyte NM_013448 /// NM_182648 growth factor receptor, craniofacial dysostosis 1, Crouzon syndrome, Pfeiffer 203638_s_at 2.10 down 1.01 down FGFR2 syndrome, Jackson-Weiss syndrome) NM_000141 /// NM_022970 1570445_a_at 2.07 down 1.01 down LOC643201 hypothetical protein LOC643201 XM_001716444 /// XM_001717933 /// XM_932161 231763_at 3.05 down 1.02 down POLR3A polymerase (RNA) III (DNA directed) polypeptide A, 155kDa NM_007055 1555368_x_at 2.08 down 1.04 down ZNF479 zinc finger protein 479 NM_033273 /// XM_001714591 /// XM_001719979 241627_x_at 2.15 down 1.05 down FLJ10357 hypothetical protein FLJ10357 NM_018071 223208_at 2.17 down 1.06 down KCTD10 potassium channel tetramerisation domain containing 10 NM_031954 219923_at 2.09 down 1.07 down TRIM45 tripartite motif-containing 45 NM_025188 242772_x_at 2.03 down 1.07 down Transcribed locus 233019_at 2.19 down 1.08 down CNOT7 CCR4-NOT transcription complex, subunit 7 NM_013354 -
393LN V 393P 344SQ V 393P Probe Set Entrez Gene
393LN v 393P 344SQ v 393P Entrez fold fold probe set Gene Gene Symbol Gene cluster Gene Title p-value change p-value change chemokine (C-C motif) ligand 21b /// chemokine (C-C motif) ligand 21a /// chemokine (C-C motif) ligand 21c 1419426_s_at 18829 /// Ccl21b /// Ccl2 1 - up 393 LN only (leucine) 0.0047 9.199837 0.45212 6.847887 nuclear factor of activated T-cells, cytoplasmic, calcineurin- 1447085_s_at 18018 Nfatc1 1 - up 393 LN only dependent 1 0.009048 12.065 0.13718 4.81 RIKEN cDNA 1453647_at 78668 9530059J11Rik1 - up 393 LN only 9530059J11 gene 0.002208 5.482897 0.27642 3.45171 transient receptor potential cation channel, subfamily 1457164_at 277328 Trpa1 1 - up 393 LN only A, member 1 0.000111 9.180344 0.01771 3.048114 regulating synaptic membrane 1422809_at 116838 Rims2 1 - up 393 LN only exocytosis 2 0.001891 8.560424 0.13159 2.980501 glial cell line derived neurotrophic factor family receptor alpha 1433716_x_at 14586 Gfra2 1 - up 393 LN only 2 0.006868 30.88736 0.01066 2.811211 1446936_at --- --- 1 - up 393 LN only --- 0.007695 6.373955 0.11733 2.480287 zinc finger protein 1438742_at 320683 Zfp629 1 - up 393 LN only 629 0.002644 5.231855 0.38124 2.377016 phospholipase A2, 1426019_at 18786 Plaa 1 - up 393 LN only activating protein 0.008657 6.2364 0.12336 2.262117 1445314_at 14009 Etv1 1 - up 393 LN only ets variant gene 1 0.007224 3.643646 0.36434 2.01989 ciliary rootlet coiled- 1427338_at 230872 Crocc 1 - up 393 LN only coil, rootletin 0.002482 7.783242 0.49977 1.794171 expressed sequence 1436585_at 99463 BB182297 1 - up 393 -
Catenin Signaling in the Liver Petr Protiva,1,2,* Jingjing Gong,1,* Bharath Sreekumar,2 Richard Torres,3 Xuchen Zhang,2 Glenn S
ORIGINAL RESEARCH Pigment Epithelium-Derived Factor (PEDF) Inhibits Wnt/b-catenin Signaling in the Liver Petr Protiva,1,2,* Jingjing Gong,1,* Bharath Sreekumar,2 Richard Torres,3 Xuchen Zhang,2 Glenn S. Belinsky,1 Mona Cornwell,4 Susan E. Crawford,4 Yasuko Iwakiri,1 and Chuhan Chung1,2 1Department of Medicine, Yale University School of Medicine, New Haven, Connecticut; 2VA CT Healthcare System, West Haven, Connecticut; 3Department of Laboratory Medicine, Yale University School of Medicine, New Haven, Connecticut; 4Department of Pathology, St. Louis University School of Medicine, St. Louis, Missouri SUMMARY Keywords: Extracellular Matrix; PEDF; Wnt/b-Catenin. The absence of pigment epithelium-derived factor (PEDF) in epatocellular carcinoma (HCC) is a major cause of hepatocellular carcinoma (HCC) enhances Wnt/b-catenin cancer-related deaths worldwide.1 Genomic signaling. Genomic profiling of PEDF knockout livers corre- H fi fi “ ” lates with gene expression signatures of human HCC asso- pro ling has classi ed HCC based on molecular signatures ciated with aberrant Wnt/b-catenin signaling. PEDF is an that correlate with biological characteristics and clinical 2,3 fi endogenous inhibitor of Wnt/b-catenin signaling. outcomes. One nding from these studies is the role of the extracellular matrix (ECM) in determining tumor behav- – ior.4 6 For instance, modulators of the ECM can activate b BACKGROUND & AIMS: Pigment epithelium-derived factor developmental pathways such as Wnt/ -catenin signaling, fi (PEDF) is a secretory protein that inhibits multiple tumor types. thereby connecting liver brosis to a signaling pathway that 3 PEDF inhibits the Wnt coreceptor, low-density lipoprotein drives hepatocarcinogenesis. -
Mycobacterium Tuberculosis Induced Transcription in Macrophages: the Role of TPL2/ERK Signalling in the Negative Regulation of T
Mycobacterium tuberculosis induced transcription in macrophages: the role of TPL2/ERK signalling in the negative regulation of type I interferon production and implications for control of tuberculosis John Benson Ewbank August 2012 Division of Immunoregulation MRC National Institute for Medical Research The Ridgeway, Mill Hill London NW7 1AA Submitted to University College London for the Degree of Doctor of Philosophy I, John Benson Ewbank, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis Abstract Abstract Mycobacterium tuberculosis is an important global cause of mortality and morbidity. The major host cell of Mycobacterium tuberculosis is the macrophage, and Mycobacterium tuberculosis is able to subvert the macrophage response in order to survive and replicate. The majority of infected individuals mount an immune response capable of controlling Mycobacterium tuberculosis infection. This requires the cytokines IL-12, TNFα, IL-1 and IFNγ, which promote eradication or control of infection. However, other immune factors, including IL-10 and type I IFN, can inhibit this protective response. In this study we have used microarray analysis to study the temporal response of macrophages to Mycobacterium tuberculosis infection, in an unbiased fashion. In response to Mycobacterium tuberculosis infection, macrophages produced cytokines and chemokines, upregulated genes involved with major histocompatability class I antigen presentation, activated both pro- and anti-apoptotic genes and downregulated many genes involved in cell-division and metabolism. We also observed the early induction of genes regulated by the extracellular-regulated kinase (ERK) MAP kinase pathway, and the upregulation of genes known to be induced by type I IFN, leading us to further investigate the role of these pathways in the macrophage response to Mycobacterium tuberculosis. -
Enriched Genes FLX07
enriched genes FLX07 Entrez Symbols Name TermID TermDesc 24950 MGC156498,S5AR 1,Srd5a1 steroid-5-alpha-reductase, alpha polypeptide 1 (3-oxo-5 alpha-steroid delta 4-dehydrogenase alpha 1) GO:0003865 3-oxo-5-alpha-steroid 4-dehydrogenase activity 361191 Nsun2,RGD1311954 NOL1/NOP2/Sun domain family, member 2 GO:0003865 3-oxo-5-alpha-steroid 4-dehydrogenase activity 305291 RGD1308828,S5AR 3,Srd5a3 steroid 5 alpha-reductase 3 GO:0003865 3-oxo-5-alpha-steroid 4-dehydrogenase activity 311569 Acas2,Acss2 acyl-CoA synthetase short-chain family member 2 GO:0003987 acetate-CoA ligase activity 296259 Acas2l,Acss1 acyl-CoA synthetase short-chain family member 1 GO:0003987 acetate-CoA ligase activity 25288 ACS,Acas,Acsl1,COAA,Facl2 acyl-CoA synthetase long-chain family member 1 GO:0003987 acetate-CoA ligase activity 114024 Acs3,Acsl3,Facl3 acyl-CoA synthetase long-chain family member 3 GO:0003987 acetate-CoA ligase activity 299002 G2e3,RGD1310263 G2/M-phase specific E3 ubiquitin ligase GO:0016881 acid-amino acid ligase activity 361866 Hace1 HECT domain and ankyrin repeat containing, E3 ubiquitin protein ligase 1 GO:0016881 acid-amino acid ligase activity 316395 Hecw2 HECT, C2 and WW domain containing E3 ubiquitin protein ligase 2 GO:0016881 acid-amino acid ligase activity 309758 Herc4 hect domain and RLD 4 GO:0016881 acid-amino acid ligase activity 361815 MGC116114,Rnf8 ring finger protein 8 GO:0016881 acid-amino acid ligase activity 298576 Mul1,RGD1309944 mitochondrial ubiquitin ligase activator of NFKB 1 GO:0016881 acid-amino acid ligase activity -
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. -
1 Imipramine Treatment and Resiliency Exhibit Similar
Imipramine Treatment and Resiliency Exhibit Similar Chromatin Regulation in the Mouse Nucleus Accumbens in Depression Models Wilkinson et al. Supplemental Material 1. Supplemental Methods 2. Supplemental References for Tables 3. Supplemental Tables S1 – S24 SUPPLEMENTAL TABLE S1: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S2: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S3: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S4: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Isolation Model (p<0.001) SUPPLEMENTAL TABLE S5: Genes Demonstrating Common Altered Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S6: Genes Demonstrating Increased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S7: Genes Demonstrating Decreased Repressive DimethylK9/K27-H3 Methylation in the Social Defeat and Social Isolation Models (p<0.001) SUPPLEMENTAL TABLE S8: Genes Demonstrating Increased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S9: Genes Demonstrating Decreased Phospho-CREB Binding in the Social Defeat Model (p<0.001) SUPPLEMENTAL TABLE S10: Genes Demonstrating Increased Phospho-CREB Binding in the Social -
Impact of MLL5 Expression on Decitabine Efficacy and DNA Methylation in Acute Myeloid Leukemia
Acute Myeloid Leukemia SUPPLEMENTARY APPENDIX Impact of MLL5 expression on decitabine efficacy and DNA methylation in acute myeloid leukemia Haiyang Yun,1 Frederik Damm,2 Damian Yap,3,4 Adrian Schwarzer,5 Anuhar Chaturvedi,1 Nidhi Jyotsana,1 Michael Lübbert,6 Lars Bullinger,7 Konstanze Döhner,7 Robert Geffers,8 Samuel Aparicio,3,4 R. Keith Humphries,9,10 Arnold Ganser,1 and Michael Heuser1 1Department of Hematology, Hemostasis, Oncology and Stem cell Transplantation, Hannover Medical School, Germany; 2Department of Hematology, Oncology, and Tumor Immunology, Charité, Berlin, Germany; 3Department of Molecular Oncology, British Columbia Cancer Agency, Vancouver, BC, Canada; 4Department of Pathology and Laboratory Medi- cine, University of British Columbia, Vancouver, BC, Canada; 5Institute of Experimental Hematology, Hannover Medical School, Germany; 6Division of Hematology and Oncology, University of Freiburg Medical Center, Germany; 7Department of Internal Medicine III, University Hospital of Ulm, Germany; 8Department of Cell Biology and Immunology, Helmholtz Centre for Infection Research, Braunschweig, Germany; 9Terry Fox Laboratory, British Columbia Cancer Agency, Vancou- ver, BC, Canada; and 10Department of Medicine, University of British Columbia, Vancouver, BC, Canada ©2014 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2013.101386 *These authors contributed equally to this work. †These authors contributed equally to this work. Manuscript received on November 19, 2013. Manuscript accepted on May 23, 2014. Correspondence: [email protected] Impact of MLL5 expression on decitabine efficacy and DNA methylation in acute myeloid leukemia Haiyang Yun1, Frederik Damm2, Damian Yap3,4, Adrian Schwarzer5, Anuhar Chaturvedi1, Nidhi Jyotsana1, Michael Lübbert6, Lars Bullinger7, Konstanze Döhner7, Robert Geffers8, Samuel Aparicio3,4, R. -
Tracking Profiles of Genomic Instability in Spontaneous Transformation and Tumorigenesis Lesley Lawrenson Wayne State University
Wayne State University Wayne State University Dissertations 1-1-2010 Tracking profiles of genomic instability in spontaneous transformation and tumorigenesis Lesley Lawrenson Wayne State University, Follow this and additional works at: http://digitalcommons.wayne.edu/oa_dissertations Part of the Bioinformatics Commons, Genetics Commons, and the Molecular Biology Commons Recommended Citation Lawrenson, Lesley, "Tracking profiles of genomic instability in spontaneous transformation and tumorigenesis" (2010). Wayne State University Dissertations. Paper 492. This Open Access Dissertation is brought to you for free and open access by DigitalCommons@WayneState. It has been accepted for inclusion in Wayne State University Dissertations by an authorized administrator of DigitalCommons@WayneState. TRACKING PROFILES OF GENOMIC INSTABILITY IN SPONTANEOUS TRANSFORMATION AND TUMORIGENESIS by LESLEY EILEEN LAWRENSON DISSERTATION Submitted to the Graduate School of Wayne State University Detroit, Michigan in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY 2010 MAJOR: MOLECULAR MEDICINE AND GENETICS Approved by: Advisor Date © COPYRIGHT BY LESLEY LAWRENSON 2010 All Rights Reserved DEDICATION This work is dedicated to my husband, family, friends, mentors, and colleagues with deepest gratitude for their guidance and support. ii ACKNOWLEDGEMENTS The submission of this dissertation brings to an end a wonderful period in which I was a graduate student in Molecular Medicine and Genetics at Wayne State University School of Medicine. Along this path, my mentors, friends and family have helped me grow in sharing with me the many joyous moments as well as the challenges presented throughout the development of this work. I am forever indebted to those who encouraged me to continue to pursue my education. -
SUPPLEMENTAL METHODS Negative Selection of Human
SUPPLEMENTAL METHODS Negative selection of human primary CD4 T cells. Buffy coats were incubated with 1/10 volume of RosetteSep CD4 T cell enrichment cocktail (StemCell Technologies Inc., Vancouver, Canada) at room temperature for 20 min and diluted with one volume of phosphate buffered saline (PBS) containing 2% human AB serum (2% HAB/PBS). CD4 T cells were separated from the remainder of peripheral blood mononuclear cells (PBMCs) and red cell rosettes by Ficoll (Histopaque-1077, Sigma Chemical Company, St. Louis, MO) density gradient centrifugation and washed twice with 2% HAB/PBS. Cell pellets were resuspended in RPMI 1640 medium supplemented with 2 mM glutamine, 100 U/ml penicillin/100 μg/ml streptomycin, and 5% human AB serum, and left at 37oC overnight prior to histone deacetylase inhibitor (HDACi) treatment the next day. Analysis of microarray gene expression data. The quality of microarray data was assessed by constructing MA-plots using the affyPLM package [1] and by unsupervised clustering. The Bioconductor package lumi [2] was used to transform (i.e. variance-stabilizing) and normalize (i.e. robust-spline) the data and remove genes not expressed in any of the samples. Technical batch effects were removed using ComBat [3]. Paired multivariate permutation tests implemented in BRB-Array Tools (version 4.2.1) [4] under default settings (80% confident no more than 10% false positives) were used to identify genes significantly differentially expressed between SAHA treated and untreated samples. Pathway analysis was performed using gene set expression comparison tool in BRB-Array Tools. All pre-defined Kyoto Encyclopedia of Genes and Genomes (KEGG) [5, 6] and BioCarta pathways (http://cgap.nci.nih.gov/Pathways/BioCarta_Pathways) were analyzed between SAHA-treated and untreated samples.