The Genetic Regulation of Size Variation in the Transcriptome of The
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ABSTRACT ANGSTADT, ANDREA Y. Evaluation of the Genomic
ABSTRACT ANGSTADT, ANDREA Y. Evaluation of the Genomic Aberrations in Canine Osteosarcoma and Their Resemblance to the Human Counterpart. (Under the direction of Dr. Matthew Breen). In the last decade the domestic dog has emerged as an ideal biomedical model of complex genetic diseases such as cancers. Cancer in the dog occurs spontaneously and several studies have concluded that human and canine cancers have similar characteristics such as presentation of disease, rate of metastases, genetic dysregulation, and survival rates. Furthermore, in the genomic era the dog genome was found more homologous in sequence conservation to humans than mice, making it a valuable model organism for genetic study in addition to pathophysiological analysis. Osteosarcoma (OS), the most commonly diagnosed malignant bone tumor in humans and dogs, is one such cancer that would benefit from comparative genomic analysis. In humans, OS is a rare cancer diagnosed in fewer than 1,000 people per year in the USA, while in the domestic dog population the annual number of new cases is estimated to far exceed 10,000. This high rate of disease occurrence in dogs provides a unique opportunity to study the genomic imbalances in canine OS and their translational value to human OS as a means to identify important alterations involved in disease etiology. OS in humans is characterized by extremely complex karyotypes which contain both structural changes (translocations and/or rearrangements) and DNA copy number changes. Metaphase and array comparative genomic hybridization (aCGH) has assisted in uncovering the genetic imbalances that are associated with human OS phenotype. In dog OS, previous low-resolution (10-20Mb) aCGH analysis identified a wide range of recurrent copy number aberrations (CNAs), indicative of a similar level of genomic instability to human OS. -
IDENTIFICATION of CELL SURFACE MARKERS WHICH CORRELATE with SALL4 in a B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA with T(8;14)
IDENTIFICATION of CELL SURFACE MARKERS WHICH CORRELATE WITH SALL4 in a B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA WITH T(8;14) DISCOVERED THROUGH BIOINFORMATIC ANALYSIS of MICROARRAY GENE EXPRESSION DATA The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:38962442 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA ,'(17,),&$7,21 2) &(// 685)$&( 0$5.(56 :+,&+ &255(/$7( :,7+ 6$// ,1 $ %&(// $&87( /<03+2%/$67,& /(8.(0,$ :,7+ W ',6&29(5(' 7+528*+ %,2,1)250$7,& $1$/<6,6 2) 0,&52$55$< *(1( (;35(66,21 '$7$ 52%(57 3$8/ :(,1%(5* $ 7KHVLV 6XEPLWWHG WR WKH )DFXOW\ RI 7KH +DUYDUG 0HGLFDO 6FKRRO LQ 3DUWLDO )XOILOOPHQW RI WKH 5HTXLUHPHQWV IRU WKH 'HJUHH RI 0DVWHU RI 0HGLFDO 6FLHQFHV LQ ,PPXQRORJ\ +DUYDUG 8QLYHUVLW\ %RVWRQ 0DVVDFKXVHWWV -XQH Thesis Advisor: Dr. Li Chai Author: Robert Paul Weinberg Department of Pathology Candidate MMSc in Immunology Brigham and Womens’ Hospital Harvard Medical School 77 Francis Street 25 Shattuck Street Boston, MA 02215 Boston, MA 02215 IDENTIFICATION OF CELL SURFACE MARKERS WHICH CORRELATE WITH SALL4 IN A B-CELL ACUTE LYMPHOBLASTIC LEUKEMIA WITH TRANSLOCATION t(8;14) DISCOVERED THROUGH BIOINFORMATICS ANALYSIS OF MICROARRAY GENE EXPRESSION DATA Abstract Acute Lymphoblastic Leukemia (ALL) is the most common leukemia in children, causing signficant morbidity and mortality annually in the U.S. -
PRODUCT SPECIFICATION Anti-C12orf43
Anti-C12orf43 Product Datasheet Polyclonal Antibody PRODUCT SPECIFICATION Product Name Anti-C12orf43 Product Number HPA046148 Gene Description chromosome 12 open reading frame 43 Clonality Polyclonal Isotype IgG Host Rabbit Antigen Sequence Recombinant Protein Epitope Signature Tag (PrEST) antigen sequence: AWGLEQRPHVAGKPRAGAANSQLSTSQPSLRHKVNEHEQDGNELQTTPEF RAHVAKKLGALLDSFITISEAAKEPAKAKVQKVALEDDGFRLFFTSVPGG REKEESPQPR Purification Method Affinity purified using the PrEST antigen as affinity ligand Verified Species Human Reactivity Recommended IHC (Immunohistochemistry) Applications - Antibody dilution: 1:50 - 1:200 - Retrieval method: HIER pH6 WB (Western Blot) - Working concentration: 0.04-0.4 µg/ml ICC-IF (Immunofluorescence) - Fixation/Permeabilization: PFA/Triton X-100 - Working concentration: 0.25-2 µg/ml Characterization Data Available at atlasantibodies.com/products/HPA046148 Buffer 40% glycerol and PBS (pH 7.2). 0.02% sodium azide is added as preservative. Concentration Lot dependent Storage Store at +4°C for short term storage. Long time storage is recommended at -20°C. Notes Gently mix before use. Optimal concentrations and conditions for each application should be determined by the user. For protocols, additional product information, such as images and references, see atlasantibodies.com. Product of Sweden. For research use only. Not intended for pharmaceutical development, diagnostic, therapeutic or any in vivo use. No products from Atlas Antibodies may be resold, modified for resale or used to manufacture commercial products without prior written approval from Atlas Antibodies AB. Warranty: The products supplied by Atlas Antibodies are warranted to meet stated product specifications and to conform to label descriptions when used and stored properly. Unless otherwise stated, this warranty is limited to one year from date of sales for products used, handled and stored according to Atlas Antibodies AB's instructions. -
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. -
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Supplementary Figure S1. Results of flow cytometry analysis, performed to estimate CD34 positivity, after immunomagnetic separation in two different experiments. As monoclonal antibody for labeling the sample, the fluorescein isothiocyanate (FITC)- conjugated mouse anti-human CD34 MoAb (Mylteni) was used. Briefly, cell samples were incubated in the presence of the indicated MoAbs, at the proper dilution, in PBS containing 5% FCS and 1% Fc receptor (FcR) blocking reagent (Miltenyi) for 30 min at 4 C. Cells were then washed twice, resuspended with PBS and analyzed by a Coulter Epics XL (Coulter Electronics Inc., Hialeah, FL, USA) flow cytometer. only use Non-commercial 1 Supplementary Table S1. Complete list of the datasets used in this study and their sources. GEO Total samples Geo selected GEO accession of used Platform Reference series in series samples samples GSM142565 GSM142566 GSM142567 GSM142568 GSE6146 HG-U133A 14 8 - GSM142569 GSM142571 GSM142572 GSM142574 GSM51391 GSM51392 GSE2666 HG-U133A 36 4 1 GSM51393 GSM51394 only GSM321583 GSE12803 HG-U133A 20 3 GSM321584 2 GSM321585 use Promyelocytes_1 Promyelocytes_2 Promyelocytes_3 Promyelocytes_4 HG-U133A 8 8 3 GSE64282 Promyelocytes_5 Promyelocytes_6 Promyelocytes_7 Promyelocytes_8 Non-commercial 2 Supplementary Table S2. Chromosomal regions up-regulated in CD34+ samples as identified by the LAP procedure with the two-class statistics coded in the PREDA R package and an FDR threshold of 0.5. Functional enrichment analysis has been performed using DAVID (http://david.abcc.ncifcrf.gov/) -
Identification of RNA Binding Proteins Associated with Dengue Virus RNA in Infected Cells Reveals Temporally Distinct Host Factor Requirements
RESEARCH ARTICLE Identification of RNA Binding Proteins Associated with Dengue Virus RNA in Infected Cells Reveals Temporally Distinct Host Factor Requirements Olga V. Viktorovskaya1, Todd M. Greco2, Ileana M. Cristea2, Sunnie R. Thompson1* 1 Department of Microbiology, University of Alabama at Birmingham, Birmingham, Alabama, United States of America, 2 Department of Molecular Biology, Princeton University, Princeton, New Jersey, United States of America a11111 * [email protected] Abstract OPEN ACCESS Background Citation: Viktorovskaya OV, Greco TM, Cristea IM, There are currently no vaccines or antivirals available for dengue virus infection, which can Thompson SR (2016) Identification of RNA Binding cause dengue hemorrhagic fever and death. A better understanding of the host pathogen Proteins Associated with Dengue Virus RNA in interaction is required to develop effective therapies to treat DENV. In particular, very little is Infected Cells Reveals Temporally Distinct Host Factor Requirements. PLoS Negl Trop Dis 10(8): known about how cellular RNA binding proteins interact with viral RNAs. RNAs within cells e0004921. doi:10.1371/journal.pntd.0004921 are not naked; rather they are coated with proteins that affect localization, stability, transla- Editor: Aravinda M de Silva, University of North tion and (for viruses) replication. Carolina at Chapel Hill, UNITED STATES Received: March 30, 2016 Methodology/Principal Findings Accepted: July 22, 2016 Seventy-nine novel RNA binding proteins for dengue virus (DENV) were identified by cross- linking proteins to dengue viral RNA during a live infection in human cells. These cellular pro- Published: August 24, 2016 teins were specific and distinct from those previously identified for poliovirus, suggesting a Copyright: © 2016 Viktorovskaya et al. -
Noelia Díaz Blanco
Effects of environmental factors on the gonadal transcriptome of European sea bass (Dicentrarchus labrax), juvenile growth and sex ratios Noelia Díaz Blanco Ph.D. thesis 2014 Submitted in partial fulfillment of the requirements for the Ph.D. degree from the Universitat Pompeu Fabra (UPF). This work has been carried out at the Group of Biology of Reproduction (GBR), at the Department of Renewable Marine Resources of the Institute of Marine Sciences (ICM-CSIC). Thesis supervisor: Dr. Francesc Piferrer Professor d’Investigació Institut de Ciències del Mar (ICM-CSIC) i ii A mis padres A Xavi iii iv Acknowledgements This thesis has been made possible by the support of many people who in one way or another, many times unknowingly, gave me the strength to overcome this "long and winding road". First of all, I would like to thank my supervisor, Dr. Francesc Piferrer, for his patience, guidance and wise advice throughout all this Ph.D. experience. But above all, for the trust he placed on me almost seven years ago when he offered me the opportunity to be part of his team. Thanks also for teaching me how to question always everything, for sharing with me your enthusiasm for science and for giving me the opportunity of learning from you by participating in many projects, collaborations and scientific meetings. I am also thankful to my colleagues (former and present Group of Biology of Reproduction members) for your support and encouragement throughout this journey. To the “exGBRs”, thanks for helping me with my first steps into this world. Working as an undergrad with you Dr. -
Variation in Protein Coding Genes Identifies Information
bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. 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-NC-ND 4.0 International license. Animal complexity and information flow 1 1 2 3 4 5 Variation in protein coding genes identifies information flow as a contributor to 6 animal complexity 7 8 Jack Dean, Daniela Lopes Cardoso and Colin Sharpe* 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Institute of Biological and Biomedical Sciences 25 School of Biological Science 26 University of Portsmouth, 27 Portsmouth, UK 28 PO16 7YH 29 30 * Author for correspondence 31 [email protected] 32 33 Orcid numbers: 34 DLC: 0000-0003-2683-1745 35 CS: 0000-0002-5022-0840 36 37 38 39 40 41 42 43 44 45 46 47 48 49 Abstract bioRxiv preprint doi: https://doi.org/10.1101/679456; this version posted June 21, 2019. 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-NC-ND 4.0 International license. Animal complexity and information flow 2 1 Across the metazoans there is a trend towards greater organismal complexity. How 2 complexity is generated, however, is uncertain. Since C.elegans and humans have 3 approximately the same number of genes, the explanation will depend on how genes are 4 used, rather than their absolute number. -
Plasma Fatty Acid Ratios Affect Blood Gene Expression Profiles - a Cross-Sectional Study of the Norwegian Women and Cancer Post-Genome Cohort
Plasma Fatty Acid Ratios Affect Blood Gene Expression Profiles - A Cross-Sectional Study of the Norwegian Women and Cancer Post-Genome Cohort Karina Standahl Olsen1*, Christopher Fenton2, Livar Frøyland3, Marit Waaseth4, Ruth H. Paulssen2, Eiliv Lund1 1 Department of Community Medicine, University of Tromsø, Tromsø, Norway, 2 Department of Clinical Medicine, University of Tromsø, Tromsø, Norway, 3 National Institute of Nutrition and Seafood Research (NIFES), Bergen, Norway, 4 Department of Pharmacy, University of Tromsø, Tromsø, Norway Abstract High blood concentrations of n-6 fatty acids (FAs) relative to n-3 FAs may lead to a ‘‘physiological switch’’ towards permanent low-grade inflammation, potentially influencing the onset of cardiovascular and inflammatory diseases, as well as cancer. To explore the potential effects of FA ratios prior to disease onset, we measured blood gene expression profiles and plasma FA ratios (linoleic acid/alpha-linolenic acid, LA/ALA; arachidonic acid/eicosapentaenoic acid, AA/EPA; and total n-6/n-3) in a cross-section of middle-aged Norwegian women (n = 227). After arranging samples from the highest values to the lowest for all three FA ratios (LA/ALA, AA/EPA and total n-6/n-3), the highest and lowest deciles of samples were compared. Differences in gene expression profiles were assessed by single-gene and pathway-level analyses. The LA/ALA ratio had the largest impact on gene expression profiles, with 135 differentially expressed genes, followed by the total n-6/ n-3 ratio (125 genes) and the AA/EPA ratio (72 genes). All FA ratios were associated with genes related to immune processes, with a tendency for increased pro-inflammatory signaling in the highest FA ratio deciles. -
Rapid, Direct Detection of Bacterial Topoisomerase 1-DNA Adducts by RADAR/ELISA
bioRxiv preprint doi: https://doi.org/10.1101/2020.03.09.984153; this version posted March 10, 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-NC-ND 4.0 International license. Rapid, direct detection of bacterial Topoisomerase 1-DNA adducts by RADAR/ELISA Devapriya Sinha1,*, Kostantin Kiianitsa1,*, David R. Sherman2, Nancy Maizels1,3 1Department of Immunology, University of Washington, 1959 NE Pacific St., Seattle, WA 98195, USA 2Department of Microbiology, University of Washington, 815 Republican St., Seattle, WA 98102, USA 3Department of Biochemistry, University of Washington, 1959 NE Pacific St., Seattle, WA 98195, USA *The authors wish it to be known that, in their opinion, the first two authors should be regarded as Joint First Authors. To whom correspondence should be addressed. Tel., +1 206-685-4449; Fax: +1 206- 221-6781; Email: [email protected] Running title: Direct Assay of Bacterial Top1-DNA Adducts Keywords: DNA-protein crosslinK, gyrase, Mycobacteria, tuberculosis, antibiotic, topoisomerase poison 1 Abstract 2 Topoisomerases are proven drug targets, but antibiotics that poison bacterial 3 Topoisomerase 1 (Top1) have yet to be discovered. We have developed a rapid and 4 direct assay for quantification of Top1-DNA adducts that is suitable for high throughput 5 assays. Adducts are recovered by "RADAR fractionation", a quick, convenient 6 approach in which cells are lysed in chaotropic salts and detergent and nucleic acids 7 and covalently bound adducts then precipitated with alcohol. -
An Important Region in Coronary Artery Disease: a Panel Approach to Investigation of the Coronary Artery Disease Etiology
Int J Cardiovasc Pract Review Article April 2019, Volume 4, Issue 2 (21-35) 9P21.3 locus; An Important Region in Coronary Artery Disease: A Panel Approach to Investigation of the Coronary Artery Disease Etiology Soodeh Omidi 1, Fatemeh Ebrahimzadeh 2, Samira Kalayinia 3,* 1 Department of Genetic, Faculty of Advanced Medical Technologies, Golestan University of Medical Science (GUMS), Gorgan, Iran 2 Department of Medical Biotechnology, School of Medicine, Zanjan University of Medical Sciences (ZUMS), Zanjan, Iran 3 Cardiogenetics Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran * Corresponding author: Samira Kalayinia, Ph.D. Cardiogenetics Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical DOI: 10.29252/ijcp-25001 Sciences, Tehran, Iran. Tel: +98-2123923033, Fax: +98-2122663213, E-mail: [email protected] Submitted: 07-04-2019 Abstract Accepted: 06-05-2019 Coronary artery disease (CAD) is a disease of major concern worldwide. It is the main Keywords: cause of mortality in many societies and improving the understanding about the CAD Etiology mechanism, progression and treatment, is necessary. Recent discovery of genetic factors Heart Disease underlying CAD has improved our knowledge of the disease in support of well-known Genome Wide Association traditional risk factors. Genotype-environment interaction is known as the main risk Study factor. Loci on many different chromosomes have been identified as a risk factors that © 2019. International Journal increase CAD susceptibility. Here we performed a comprehensive literature review of Cardiovascular Practice. pinpointing hotspot loci involved in CAD pathogenicity. The 9p21.3 locus is the most common region associated with CAD and its specific structure and function have been remarkable in many studies. -
Nº Ref Uniprot Proteína Péptidos Identificados Por MS/MS 1 P01024
Document downloaded from http://www.elsevier.es, day 26/09/2021. This copy is for personal use. Any transmission of this document by any media or format is strictly prohibited. Nº Ref Uniprot Proteína Péptidos identificados 1 P01024 CO3_HUMAN Complement C3 OS=Homo sapiens GN=C3 PE=1 SV=2 por 162MS/MS 2 P02751 FINC_HUMAN Fibronectin OS=Homo sapiens GN=FN1 PE=1 SV=4 131 3 P01023 A2MG_HUMAN Alpha-2-macroglobulin OS=Homo sapiens GN=A2M PE=1 SV=3 128 4 P0C0L4 CO4A_HUMAN Complement C4-A OS=Homo sapiens GN=C4A PE=1 SV=1 95 5 P04275 VWF_HUMAN von Willebrand factor OS=Homo sapiens GN=VWF PE=1 SV=4 81 6 P02675 FIBB_HUMAN Fibrinogen beta chain OS=Homo sapiens GN=FGB PE=1 SV=2 78 7 P01031 CO5_HUMAN Complement C5 OS=Homo sapiens GN=C5 PE=1 SV=4 66 8 P02768 ALBU_HUMAN Serum albumin OS=Homo sapiens GN=ALB PE=1 SV=2 66 9 P00450 CERU_HUMAN Ceruloplasmin OS=Homo sapiens GN=CP PE=1 SV=1 64 10 P02671 FIBA_HUMAN Fibrinogen alpha chain OS=Homo sapiens GN=FGA PE=1 SV=2 58 11 P08603 CFAH_HUMAN Complement factor H OS=Homo sapiens GN=CFH PE=1 SV=4 56 12 P02787 TRFE_HUMAN Serotransferrin OS=Homo sapiens GN=TF PE=1 SV=3 54 13 P00747 PLMN_HUMAN Plasminogen OS=Homo sapiens GN=PLG PE=1 SV=2 48 14 P02679 FIBG_HUMAN Fibrinogen gamma chain OS=Homo sapiens GN=FGG PE=1 SV=3 47 15 P01871 IGHM_HUMAN Ig mu chain C region OS=Homo sapiens GN=IGHM PE=1 SV=3 41 16 P04003 C4BPA_HUMAN C4b-binding protein alpha chain OS=Homo sapiens GN=C4BPA PE=1 SV=2 37 17 Q9Y6R7 FCGBP_HUMAN IgGFc-binding protein OS=Homo sapiens GN=FCGBP PE=1 SV=3 30 18 O43866 CD5L_HUMAN CD5 antigen-like OS=Homo