Chromatin Remodeling in Epstein-Barr Virus After Induction of the Lytic Phase: Molecular Characterization of the Role of Bzlf1 and Its Interactions

Total Page:16

File Type:pdf, Size:1020Kb

Chromatin Remodeling in Epstein-Barr Virus After Induction of the Lytic Phase: Molecular Characterization of the Role of Bzlf1 and Its Interactions DISSERTATION ZUR ERLANGUNG DES DOKTORGRADES DER FAKULTÄT FÜR BIOLOGIE DER LUDWIG-MAXIMILIANS-UNIVERSITÄT MÜNCHEN CHROMATIN REMODELING IN EPSTEIN-BARR VIRUS AFTER INDUCTION OF THE LYTIC PHASE: MOLECULAR CHARACTERIZATION OF THE ROLE OF BZLF1 AND ITS INTERACTIONS MARISA SCHÄFFNER Dissertation eingereicht am 30. April 2015 Erstgutachter: Prof. Dr. Dirk Eick Zweitgutachter: Prof. Dr. Heinrich Leonhardt Tag der mündlichen Prüfung: 26.11.2015 ERKLÄRUNG Hiermit erkläre ich, dass die vorliegende Arbeit mit dem Titel „CHROMATIN REMODELING IN EPSTEIN-BARR VIRUS AFTER INDUCTION OF THE LYTIC PHASE: MOLECULAR CHARACTERIZATION OF THE ROLE OF BZLF1 AND ITS INTERACTIONS“ von mir selbstständig und ohne unerlaubte Hilfsmittel angefertigt wurde, und ich mich dabei nur der ausdrücklich bezeichneten Quellen und Hilfsmittel bedient habe. Die Arbeit wurde weder in der jetzigen noch in einer abgewandelten Form einer anderen Prüfungskommission vorgelegt. München, 30. April 2015 Marisa Schäffner CONTENT 1. Introduction....................................................................................................................... 7 1.1 The architecture of chromatin.......................................................................................... 7 1.1.1 Nucleosomes are histone octamers ........................................................................ 7 1.1.1.1 Nucleosome components.................................................................................. 7 1.1.1.2 Histone modifications and histone variants...................................................... 8 1.1.1.3 Nucleosome positioning ................................................................................. 10 1.1.2 Enhancer-promoter contacts................................................................................. 12 1.2 Chromatin regulators and their way of functions........................................................... 14 1.2.1 Chromatin remodelers.......................................................................................... 14 1.2.2 Pioneer factors...................................................................................................... 20 1.3 Epigenetic regulation in EBV ........................................................................................ 22 1.3.1 EBV and its life cycle........................................................................................... 22 1.3.2 EBV and its lytic switch transactivator BZLF1 ................................................... 24 1.3.3 Epigenetic regulation mechanisms upon lytic reactivation.................................. 26 1.3.4 Interactions of BZLF1 with viral and host cell proteins ...................................... 28 1.4 Scope of my thesis work............................................................................................. 30 2. Material............................................................................................................................ 31 2.1 Oligonucleotides ............................................................................................................ 31 2.2 Plasmids ......................................................................................................................... 31 2.3 Antibodies...................................................................................................................... 32 2.4 Bacterial strains.............................................................................................................. 32 2.5 Eukaryotic cell lines....................................................................................................... 33 CONTENT II 2.6 Cell culture media and additives.................................................................................... 33 2.6.1 Media for the cultivation of bacteria....................................................................... 33 2.6.2 Media for the cultivation of eukaryotic cells .......................................................... 33 2.7 Chemicals and enzymes................................................................................................. 34 2.8 Buffers and solutions ..................................................................................................... 35 2.9 Commercial kits............................................................................................................. 36 2.10 Software ....................................................................................................................... 37 2.11 Devices and consumables ............................................................................................ 37 3. Methods............................................................................................................................ 38 3.1 Bacterial culture............................................................................................................. 38 3.1.1 Growth and storage of bacterial cultures ................................................................ 38 3.1.2 Transformation of bacteria...................................................................................... 38 3.2 Eukaryotic cell culture ................................................................................................... 39 3.2.1 Cell culture conditions ............................................................................................ 39 3.2.2 Storage of eukaryotic cells...................................................................................... 39 3.2.3 Transient transfection of HEK293 cells.................................................................. 39 3.2.4 Electroporation of eukaryotic cells ......................................................................... 40 3.2.5 Establishment of stable cell lines............................................................................ 40 3.2.6 Flow cytometry ....................................................................................................... 40 3.3 Nucleic acid techniques ................................................................................................. 41 3.3.1 DNA purification from E.coli................................................................................. 41 3.3.2 DNA purification from eukaryotic cells ................................................................. 41 3.3.3 Purification of DNA from PCR products and agarose gels .................................... 41 3.3.4 Electroelution of DNA from native gels................................................................. 42 3.3.5 Dephosphorylation and ligation.............................................................................. 42 3.3.6 Polymerase chain reaction (PCR) ........................................................................... 42 3.3.7 Quantitative real time PCR (qPCR)........................................................................ 42 3.3.8 Mutagenesis PCR.................................................................................................... 43 3.3.9 Isolation of RNA from cells.................................................................................... 43 3.3.10 Reverse transcription of RNA............................................................................... 44 3.4 Protein analysis techniques............................................................................................ 44 3.4.1 Preparation of whole cell extracts........................................................................... 44 3.4.2 Preparation of nuclear cell extracts......................................................................... 44 3.4.3 Purification of Strep-tag fusion proteins................................................................. 45 3.4.4 Electromobility shift assay (EMSA) for detecting protein-DNA interactions ....... 45 3.4.5 Determination of the equilibrium dissociation constant (Kd value) ....................... 46 3.4.6 Sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)........... 47 3.4.7 Western blot............................................................................................................ 47 3.4.8 Silver staining ......................................................................................................... 47 CONTENT III 3.5 Chromatin Immunoprecipitation (ChIP)........................................................................ 48 3.5.1 Chromatin preparation ............................................................................................ 48 3.5.2 Chromatin immunoprecipitation and purification of ChIP DNA ........................... 48 3.5.3 Quantitation of ChIP DNA by qPCR...................................................................... 49 3.6 Sequential ChIP (ReChIP) ............................................................................................. 49 3.6.1 Chromatin preparation for BZLF1-directed ChIP .................................................. 49 3.6.2 ReChIP starting with a BLZF1-directed antibody.................................................. 50 3.6.3 ReChIP starting with an H3K4me1-directed antibody ........................................... 52 3.7 Co-Immunoprecipitation (CoIP).................................................................................... 53 3.7.1 CoIPs of GFP-tagged bait proteins ......................................................................... 53 3.7.2 CoIPs of Strep-tagged bait proteins .......................................................................
Recommended publications
  • 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.
    [Show full text]
  • Produktinformation
    Produktinformation Diagnostik & molekulare Diagnostik Laborgeräte & Service Zellkultur & Verbrauchsmaterial Forschungsprodukte & Biochemikalien Weitere Information auf den folgenden Seiten! See the following pages for more information! Lieferung & Zahlungsart Lieferung: frei Haus Bestellung auf Rechnung SZABO-SCANDIC Lieferung: € 10,- HandelsgmbH & Co KG Erstbestellung Vorauskassa Quellenstraße 110, A-1100 Wien T. +43(0)1 489 3961-0 Zuschläge F. +43(0)1 489 3961-7 [email protected] • Mindermengenzuschlag www.szabo-scandic.com • Trockeneiszuschlag • Gefahrgutzuschlag linkedin.com/company/szaboscandic • Expressversand facebook.com/szaboscandic SANTA CRUZ BIOTECHNOLOGY, INC. C22orf31 siRNA (h): sc-72761 BACKGROUND STORAGE AND RESUSPENSION C22orf31 (chromosome 22 open reading frame 31), also known as HS747E2A Store lyophilized siRNA duplex at -20° C with desiccant. Stable for at least or bK747E2.1, is a 290 amino acid protein encoded by a gene located on one year from the date of shipment. Once resuspended, store at -20° C, human chromosome 22q12.1, which contains over 500 genes and about 49 avoid contact with RNAses and repeated freeze thaw cycles. million bases. As the second smallest human chromosome, chomosome 22 Resuspend lyophilized siRNA duplex in 330 µl of the RNAse-free water contains a wide variety of genes with numerous functions. Phelan-McDermid provided. Resuspension of the siRNA duplex in 330 µl of RNAse-free water syndrome, Neurofibromatosis type 2 and autism are associated with chromo- makes a 10 µM solution in a 10 µM Tris-HCl, pH 8.0, 20 mM NaCl, 1 mM some 22. A schizophrenia susceptibility locus has been identified on chromo- EDTA buffered solution. some 22 and studies show that 22q11 deletion symptoms include a high inci- dence of schizophrenia.
    [Show full text]
  • Chapter 2: a Technique for Generating Unbiased Whole Genome
    UC San Diego UC San Diego Electronic Theses and Dissertations Title Massively Parallel Polymerase Cloning and Genome Sequencing of Single Cells Using the Microwell Displacement Amplification System (MIDAS) / Permalink https://escholarship.org/uc/item/8kn4n1wd Author Gole, Jeffrey Publication Date 2013 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, SAN DIEGO Massively Parallel Polymerase Cloning and Genome Sequencing of Single Cells Using the Microwell Displacement Amplification System (MIDAS) A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Bioengineering by Jeffrey Gole Committee in charge: Professor Kun Zhang, Chair Professor Vineet Bafna Professor Michael Heller Professor Xiaohua Huang Professor Yu-Hwa Lo 2013 Copyright Jeffrey Gole, 2013 All rights reserved The Dissertation of Jeffrey Gole is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2013 iii DEDICATION For my parents iv TABLE OF CONTENTS SIGNATURE PAGE………………………………………………………………....iii DEDICATION ................................................................................................... iv TABLE OF CONTENTS ....................................................................................v LIST OF FIGURES.......................................................................................... vii LIST OF TABLES............................................................................................viii
    [Show full text]
  • Genome-Wide Association Analyses of Esophageal Squamous Cell Carcinoma in Chinese Identify Multiple Susceptibility Loci and Gene-Environment Interactions
    ARTICLES Genome-wide association analyses of esophageal squamous cell carcinoma in Chinese identify multiple susceptibility loci and gene-environment interactions Chen Wu1,2,13, Peter Kraft2,13, Kan Zhai1,13, Jiang Chang1,13, Zhaoming Wang3,4, Yun Li5, Zhibin Hu6, Zhonghu He7, Weihua Jia8, Christian C Abnet3, Liming Liang2, Nan Hu3, Xiaoping Miao9, Yifeng Zhou10, Zhihua Liu1, Qimin Zhan1, Yu Liu1, Yan Qiao1, Yuling Zhou1, Guangfu Jin6, Chuanhai Guo7, Changdong Lu11, Haijun Yang11, Jianhua Fu8, Dianke Yu1, Neal D Freedman3, Ti Ding12, Wen Tan1, Alisa M Goldstein3, Tangchun Wu9, Hongbing Shen6, Yang Ke7, Yixin Zeng8, Stephen J Chanock3,4, Philip R Taylor3 & Dongxin Lin1 We conducted a genome-wide association study (GWAS) and a genome-wide gene-environment interaction analysis of esophageal squamous-cell carcinoma (ESCC) in 2,031 affected individuals (cases) and 2,044 controls with independent validation in 8,092 cases and 8,620 controls. We identified nine new ESCC susceptibility loci, of which seven, at chromosomes 4q23, 16q12.1, 17q21, 22q12, 3q27, 17p13 and 18p11, had a significant marginal effect (P = 1.78 × 10−39 to P = 2.49 × 10−11) and two of which, at 2q22 and 13q33, had a significant association only in the gene–alcohol drinking interaction (gene-environment P P −11 P −8 ADH interaction ( G × E) = 4.39 × 10 and G × E = 4.80 × 10 , respectively). Variants at the 4q23 locus, which includes the P −7 cluster, each had a significant interaction with alcohol drinking in their association with ESCC risk ( G × E = 2.54 × 10 to P −2 ALDH2 G × E = 3.23 × 10 ).
    [Show full text]
  • Antibody Tools Immunohistochemistry
    Antibody Tools Immunohistochemistry $$ 250 - 150 - 100 - 75 - 50 - 37 - Western Blot 25 - 20 - 15 - 10 - 1.4 1.2 1 0.8 0.6 OD 450 0.4 Sandwich ELISA 0.2 0 0.01 0.1 1 10 100 1000 Recombinant Protein Concentration(mg/ml) Immunohistochemistry Immunofluorescence 1 2 3 250 - 150 - 100 - 75 - 50 - Immunoprecipitation 37 - 25 - 20 - 15 - 100 80 60 % of Max 40 Flow Cytometry 20 0 3 4 5 0 102 10 10 10 www.abnova.com March 2013 (Sixth Edition) Abnova Corporation www.abnova.com Email: [email protected] Address: 9F, No. 108, Jhouzih St., Neihu, Taipei 114, Taiwan Tel: + 886 2 8751 1888 Fax: + 886 2 6602 1218 Antibodies tool for IHC, Class I IVD (In Vitro Diagnostics) Cat. Num. DH0003 DH0013 DH0020 DH0015 Product Name Anti-ACTN4 monoclonal antibody Anti-ANXA5 monoclonal antibody Anti-CDH17 monoclonal antibody Anti-CLDN1 monoclonal antibody Application Immunoperoxidase of monoclonal antibody Immunoperoxidase of monoclonal antibody to Immunoperoxidase of monoclonal antibody to Immunoperoxidase of monoclonal antibody to to ACTN4 on formalin-fixed paraffin- ANXA5 on formalin-fixed paraffin-embedded CDH17 on formalin-fixed paraffin-embedded CLDN1 on formalin-fixed paraffin-embedded embedded human pancreatic cancer. [antibody human colon cancer. [antibody concentration 3 human colon cancer. [antibody concentration 3 human colon cancer. [antibody concentration 3 concentration 1.5 ug/ml] ug/ml] ug/ml] ug/ml] Cat. Num. DH0002 DH0021 DH0010 DH0017 Product Name Anti-CTH monoclonal antibody Anti-EGR1 monoclonal antibody Anti-EIF2C2 monoclonal antibody Anti-ENO1 monoclonal antibody Application Immunoperoxidase of monoclonal antibody Immunoperoxidase of monoclonal antibody Immunoperoxidase of monoclonal antibody to Immunoperoxidase of monoclonal antibody to CTH on formalin-fixed paraffin-embedded to EGR1 on formalin-fixed paraffin-embedded EIF2C2 on formalin-fixed paraffin-embedded to ENO1 on formalin-fixed paraffin-embedded human liver.
    [Show full text]
  • Accurate Mutation Annotation and Functional Prediction Enhance the Applicability of -Omics Data in Precision Medicine
    The Texas Medical Center Library DigitalCommons@TMC The University of Texas MD Anderson Cancer Center UTHealth Graduate School of The University of Texas MD Anderson Cancer Biomedical Sciences Dissertations and Theses Center UTHealth Graduate School of (Open Access) Biomedical Sciences 5-2016 Accurate mutation annotation and functional prediction enhance the applicability of -omics data in precision medicine Tenghui Chen Follow this and additional works at: https://digitalcommons.library.tmc.edu/utgsbs_dissertations Part of the Bioinformatics Commons, Computational Biology Commons, Genomics Commons, and the Medicine and Health Sciences Commons Recommended Citation Chen, Tenghui, "Accurate mutation annotation and functional prediction enhance the applicability of -omics data in precision medicine" (2016). The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access). 666. https://digitalcommons.library.tmc.edu/utgsbs_dissertations/666 This Dissertation (PhD) is brought to you for free and open access by the The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences at DigitalCommons@TMC. It has been accepted for inclusion in The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access) by an authorized administrator of DigitalCommons@TMC. For more information, please contact [email protected]. ACCURATE MUTATION ANNOTATION AND FUNCTIONAL PREDICTION
    [Show full text]
  • Ensemble of Rankers for Efficient Gene Signature Extraction in Smoke Exposure Classification Maurizio Giordano*, Kumar Parijat Tripathi and Mario Rosario Guarracino
    Giordano et al. BMC Bioinformatics 2018, 19(Suppl 2):48 https://doi.org/10.1186/s12859-018-2035-3 RESEARCH Open Access Ensemble of rankers for efficient gene signature extraction in smoke exposure classification Maurizio Giordano*, Kumar Parijat Tripathi and Mario Rosario Guarracino From Bringing Maths to Life 2017 Naples, Italy. 07-09 June 2017 Abstract Background: System toxicology aims at understanding the mechanisms used by biological systems to respond to toxicants. Such understanding can be leveraged to assess the risk of chemicals, drugs, and consumer products in living organisms. In system toxicology, machine learning techniques and methodologies are applied to develop prediction models for classification of toxicant exposure of biological systems. Gene expression data (RNA/DNA microarray) are often used to develop such prediction models. Results: The outcome of the present work is an experimental methodology to develop prediction models, based on robust gene signatures, for the classification of cigarette smoke exposure and cessation in humans. It is a result of the participation in the recent sbv IMPROVER SysTox Computational Challenge. By merging different gene selection techniques, we obtain robust gene signatures and we investigate prediction capabilities of different off-the-shelf machine learning techniques, such as artificial neural networks, linear models and support vector machines. We also predict six novel genes in our signature, and firmly believe these genes have to be further investigated as biomarkers for tobacco smoking exposure. Conclusions: The proposed methodology provides gene signatures with top-ranked performances in the prediction of the investigated classification methods, as well as new discoveries in genetic signatures for bio-markers of the smoke exposure of humans.
    [Show full text]
  • GRADY-DISSERTATION-2017.Pdf (6.311Mb)
    EFFECT OF MESENCHYMAL STEM CELLS ON EQUINE OVARIAN FOLLICULAR DEVELOPMENT AND GENE EXPRESSION A Dissertation by SICILIA TATIANA GRADY Submitted to the Office of Graduate and Professional Studies of Texas A&M University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Chair of Committee, Katrin Hinrichs Committee Members, Scott V. Dindot Qinglei Li Ashlee E. Watts Head of Department, Larry J. Suva August 2017 Major Subject: Biomedical Sciences Copyright 2017 Sicilia Tatiana Grady ABSTRACT Aging affects the reproductive efficiency of females. In rodent models, injection of mesenchymal stem cells (MSCs) improves function and induces trophic mRNA expression in ovaries compromised by chemotherapy. However, little information is available on the effect of MSCs in the aging ovary, an application which if effective in increasing fertility, would have an impact in both human and equine reproduction. The aim of the research outlined in this dissertation was to investigate this area. We hypothesized that injection of MSCs into the ovaries of old mares would increase follicle numbers and increase expression of genes related to follicle growth. We examined for the first time the use of fluorescent quantum dots (QDs) to label equine MSCs, to see if this would allow them to be tracked after injection. We found that QD-labeled MSCs retain their ability to proliferate and differentiate. The QDs were maintained in MSCs induced to differentiate into chondrocytes (non-proliferating), but the percentage of labeled cells and the fluorescence intensity decreased to essentially non-detectable within 3 to 5 days in rapidly proliferating cells. Co-culture of equine ovarian tissue with MSCs was not effective due to tissue degradation in culture; however, we used this trial to develop effective methods for isolation of RNA from the extremely fibrous equine ovarian tissue.
    [Show full text]
  • Cellular Features Predicting Susceptibility to Ferroptosis: Insights from Cancer Cell-Line Profiling
    Cellular features predicting susceptibility to ferroptosis: insights from cancer cell-line profiling Vasanthi Sridhar Viswanathan Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Graduate School of Arts and Sciences COLUMBIA UNIVERSITY 2015 © 2015 Vasanthi Sridhar Viswanathan All rights reserved ABSTRACT Cellular features predicting susceptibility to ferroptosis: insights from cancer cell-line profiling Vasanthi Sridhar Viswanathan Ferroptosis is a novel non-apoptotic, oxidative form of regulated cell death that can be triggered by diverse small-molecule ferroptosis inducers (FINs) and genetic perturbations. Current lack of insights into the cellular contexts governing sensitivity to ferroptosis has hindered both translation of FINs as anti-cancer agents for specific indications and the discovery of physiological contexts where ferroptosis may function as a form of programmed cell death. This dissertation describes the identification of cellular features predicting susceptibility to ferroptosis from data generated through a large-scale profiling experiment that screened four FINs against a panel of 860 omically-characterized cancer cell lines (Cancer Therapeutics Response Portal Version 2; CTRPv2 at http://www.broadinstitute.org/ctrp/). Using correlative approaches incorporating transcriptomic, metabolomic, proteomic, and gene-dependency feature types, I uncover both pan-lineage and lineage-specific features mediating cell-line response to FINs. The first key finding from these analyses implicates high expression of sulfur and selenium metabolic pathways in conferring resistance to FINs across lineages. In contrast, the transsulfuration pathway, which enables de novo cysteine synthesis, appears to plays a role in ferroptosis resistance in a subset of lineages. The second key finding from these studies identifies cancer cells in a high mesenchymal state as being uniquely primed to undergo ferroptosis.
    [Show full text]
  • You Can Check If Genes Are Captured by the Agilent Sureselect V5 Exome
    IIHG Clinical Exome Sequencing Test Gene Coverage • Whole Exome Sequencing is a targeted capture platform which does not capture the entire exome. Regions not captured by the exome will not be analyzed. o Please note, it is important to understand the absence of a reportable variant in a given gene does not mean there are not pathogenic variants in that gene. • Data sensitivity and specificity for exome testing is variable as gene coverage is not uniform throughout the exome. • The Agilent SureSelect XT Human All Exon v5 kit captures ~98% of Refseq coding base pairs, and >94% of the captured coding bases in the exome are covered at our depth-of-coverage minimum threshold (30 reads). • All test reports include the following information: o Regions of the Symptom Candidate Gene List which were not captured by the current exome capture platform. o Regions of the Symptom Candidate Gene List which were not sequenced to a sufficient depth of coverage to make a clinical diagnosis. • You can check if genes are captured by the Agilent Agilent SureSelect v5 exome capture, and how well those genes are typically covered here. • Explanations for the headings; • Symbol: Gene symbol • Chr: Chromosome • % Captured: the minimum portion of the gene captured by the Agilent SureSelect XT Human All Exon v5 kit. This includes all transcripts for a given gene. o 100.00% = the entire gene is captured o 0.00% = none of the gene is captured • % Covered: the minimum portion of the gene that has at least 30x average coverage when sequenced on the Illumina HiSeq2000 with 100 base pair (bp) paired-end reads for eight CEPH samples.
    [Show full text]
  • Supplementary Appendix
    Supplementary Appendix Genomic Analysis of Thymic Epithelial Tumors Identifies Novel Subtypes Associated with Distinct Clinical Features Hyun-Sung Lee1, Hee-Jin Jang1, Rohan Shah1, David Yoon1, Masatsugu Hamaji2, Ori Wald1, Ju-Seog Lee3, David J. Sugarbaker1, Bryan M. Burt1 1 Table of Contents Section Page Supplementary Methods 3 Supplementary Figure Figure S1 Genomic positions of amplifications and deletions in TCGA TETs 4 Hierarchical Clustering Analysis of mRNA Expression Data in Patients Figure S2 5 with TET (n=120) Distribution of TET molecular subtypes and 3-D plot of principal Figure S3 6 component analysis and molecular subtypes of TETs Survival of TCGA TET cohort based on Masaoka staging system to Figure S4 7 check the quality of clinical data Figure S5 GTF2I mutation and mRNA expression of GTF2I across 30 types of 8 TCGA cancer Supplementary Table Table S1 Subtype-specific mRNAs in thymic epithelial tumors 9 Table S2 Clinicopathologic Characteristics of Patients 22 Table S3 Univariable Cox Regression Analysis of molecular subtypes and 23 Disease-Free Survival in the TCGA TET Sets (n=120) Table S4 List of 220 GTF2I target gene set using known transcription factor 24 binding site motifs within the TRANSFAC® predicted transcription factor targets dataset 2 SUPPLEMENTARY METHODS Justification of Decision-Tree Approach through mutual exclusivity and principal component analysis in molecular subtypes of TETs The test for mutual exclusivity applied to groups defined by GTF2I mutation, T cell signaling signature, and SCNA revealed that each subgroup was mutually exclusive (P=3.7x10-14) (Supplementary Figure S2A). Similarly, a 3D-plot of PCA demonstrated that the molecular subgroups could be distinctly separated by GTF2I mutation, T cell signaling, and SCNA (Supplementary Figure S2B).
    [Show full text]
  • 1 Supplementary Material Figure S1. Volcano Plot of Differentially
    Supplementary material Figure S1. Volcano Plot of differentially expressed genes between preterm infants fed own mother’s milk (OMM) or pasteurized donated human milk (DHM). Table S1. The 10 most representative biological processes filtered for enrichment p- value in preterm infants. Biological Processes p-value Quantity of DEG* Transcription, DNA-templated 3.62x10-24 189 Regulation of transcription, DNA-templated 5.34x10-22 188 Transport 3.75x10-17 140 Cell cycle 1.03x10-13 65 Gene expression 3.38x10-10 60 Multicellular organismal development 6.97x10-10 86 1 Protein transport 1.73x10-09 56 Cell division 2.75x10-09 39 Blood coagulation 3.38x10-09 46 DNA repair 8.34x10-09 39 Table S2. Differential genes in transcriptomic analysis of exfoliated epithelial intestinal cells between preterm infants fed own mother’s milk (OMM) and pasteurized donated human milk (DHM). Gene name Gene Symbol p-value Fold-Change (OMM vs. DHM) (OMM vs. DHM) Lactalbumin, alpha LALBA 0.0024 2.92 Casein kappa CSN3 0.0024 2.59 Casein beta CSN2 0.0093 2.13 Cytochrome c oxidase subunit I COX1 0.0263 2.07 Casein alpha s1 CSN1S1 0.0084 1.71 Espin ESPN 0.0008 1.58 MTND2 ND2 0.0138 1.57 Small ubiquitin-like modifier 3 SUMO3 0.0037 1.54 Eukaryotic translation elongation EEF1A1 0.0365 1.53 factor 1 alpha 1 Ribosomal protein L10 RPL10 0.0195 1.52 Keratin associated protein 2-4 KRTAP2-4 0.0019 1.46 Serine peptidase inhibitor, Kunitz SPINT1 0.0007 1.44 type 1 Zinc finger family member 788 ZNF788 0.0000 1.43 Mitochondrial ribosomal protein MRPL38 0.0020 1.41 L38 Diacylglycerol
    [Show full text]