The Driver of Extreme Human-Specific Olduvai Repeat
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Evaluation of Potential Biomarkers for Ewing´S Sarcoma As Cargo of Tumor Derived Exosomes
TECHNISCHE UNIVERSITÄT MÜNCHEN Klinik und Poliklinik für Kinder- und Jugendmedizin Klinikum rechts der Isar Direktor: Univ.-Prof. Dr. St. Burdach Evaluation of potential biomarkers for Ewing´s sarcoma as cargo of tumor derived exosomes Isabella Viktoria Miller Vollständiger Abdruck der von der Fakultät für Medizin der Technischen Universität München zur Erlangung des akademischen Grades eines Doktors der Medizin genehmigten Dissertation. Vorsitzender: Univ.-Prof. Dr. E. J. Rummeny Prüfer der Dissertation: 1. Univ.-Prof. Dr. St. Burdach 2. Priv.-Doz. Dr. J. M. E. Teichert-von Lüttichau 3. Univ.-Prof. Dr. A. Krackhardt Die Dissertation wurde am 31.10.2014 bei der Technischen Universität München eingereicht und durch die Fakultät für Medizin am 03.02.2016 angenommen. Contents List of Abbreviations 6 Summary 8 1 Introduction 9 1.1 Ewing´s sarcoma . .9 1.1.1 The Ewing family of tumors . .9 1.1.2 RNA based markers for subclinical disease and their limitations . 10 1.2 Exosomes . 11 1.2.1 Biogenesis and classification . 11 1.2.2 Communication pathways . 12 1.2.3 Roles in tumorigenesis . 14 1.2.3.1 Immunosuppression . 15 1.2.3.2 Angiogenesis . 15 1.2.3.3 Modulation of the microenvironment . 15 1.2.3.4 Metastasis . 16 1.2.3.5 Drug resistance . 17 1.2.4 Diagnostic implications as tumor markers . 17 1.3 Research objectives . 24 1.3.1 Aim of the project . 24 1.3.2 Key questions . 24 2 Materials and Methods 25 2.1 Materials . 25 2.1.1 List of Manufacturers . 25 2.1.2 General materials . -
Downregulation of Nuclear and Cytoplasmic Chibby Is Associated with Advanced Cervical Cancer
6632 ONCOLOGY LETTERS 14: 6632-6644, 2017 Downregulation of nuclear and cytoplasmic Chibby is associated with advanced cervical cancer MING-CHANG YANG1,2*, SHANG-TAO CHIEN3,4*, TZU-FENG YANG2,5, SHIH-YI LIN3, TAI-MIN LEE3 and YI-REN HONG1,6,7 1 2 Department of Biological Sciences, National Sun Yat-sen University, Kaohsiung 80424; Laboratory of 3 Medical Research; Department of Pathology, Kaohsiung Armed Forces General Hospital, Kaohsiung 80284; 4Department of Medical Laboratory Sciences and Biotechnology, Fooyin University, Kaohsiung 83102; 5Department of Psychiatry, Kaohsiung Armed Forces General Hospital, Kaohsiung 80284; 6Department of Biochemistry, Faculty of Medicine, College of Medicine; 7Graduate Institute of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan, R.O.C. Received March 11, 2014; Accepted June 9, 2017 DOI: 10.3892/ol.2017.7050 Abstract. Chibby has been identified as a putative tumor tumors, in which a significantly increased level of protein suppressor and antagonist to β-catenin, thereby controlling expression was detected. Chibby may be a tumor suppressor in the Wnt signaling pathway. Chibby is typically downregulated cervical cancer, since the dysregulation of Chibby expression is in numerous types of cancer and may be associated with associated with tumorigenesis in cervical cancer. Chibby and tumorigenesis. The present study aimed at clarifying the β-catenin expression together may potentially to a biomarker following: i) Whether Chibby antagonizes β-catenin in cervical for disease progression in cervical cancer. cancer; ii) whether Chibby and β-catenin mRNA expression is associated with cancer progression; and iii) whether Chibby Introduction and β-catenin expression may be used as a biomarker. -
Novel Genetic Features of Human and Mouse Purkinje Cell Differentiation Defined by Comparative Transcriptomics
Novel genetic features of human and mouse Purkinje cell differentiation defined by comparative transcriptomics David E. Buchholza, Thomas S. Carrollb, Arif Kocabasa, Xiaodong Zhua, Hourinaz Behestia, Phyllis L. Faustc, Lauren Stalbowa, Yin Fanga, and Mary E. Hattena,1 aLaboratory of Developmental Neurobiology, The Rockefeller University, New York, NY 10065; bBioinformatics Resource Center, The Rockefeller University, New York, NY 10065; and cDepartment of Pathology and Cell Biology, Columbia University Irving Medical Center and the New York Presbyterian Hospital, New York, NY 10032 Contributed by Mary E. Hatten, April 22, 2020 (sent for review January 3, 2020; reviewed by Lorenz Studer and Hynek Wichterle) Comparative transcriptomics between differentiating human plu- is ataxia-telangiectasia, which shows massive loss of PCs in hu- ripotent stem cells (hPSCs) and developing mouse neurons offers a mans but not in the mouse (11). Human pluripotent stem cells powerful approach to compare genetic and epigenetic pathways (hPSCs) provide a complementary approach to studying human in human and mouse neurons. To analyze human Purkinje cell disease in the mouse (12–14). Validated methods to derive (PC) differentiation, we optimized a protocol to generate human specific neural subtypes from hPSCs are necessary prerequisites pluripotent stem cell-derived Purkinje cells (hPSC-PCs) that formed to disease modeling. We and others have recently developed synapses when cultured with mouse cerebellar glia and granule protocols to derive PCs from hPSCs (15–18). cells and fired large calcium currents, measured with the geneti- One limitation of most hPSC-derived central nervous system cally encoded calcium indicator jRGECO1a. To directly compare (CNS) neurons is the lack of genetic information, especially of global gene expression of hPSC-PCs with developing mouse PCs, transcriptomic signatures, to rigorously identify specific types of we used translating ribosomal affinity purification (TRAP). -
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. -
Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis
Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma, Anna-Karin Ekman, Cecilia Bivik Eding and Charlotta Enerbäck The self-archived postprint version of this journal article is available at Linköping University Institutional Repository (DiVA): http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-147791 N.B.: When citing this work, cite the original publication. Verma, D., Ekman, A., Bivik Eding, C., Enerbäck, C., (2018), Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis, Journal of Investigative Dermatology, 138(5), 1088-1093. https://doi.org/10.1016/j.jid.2017.11.036 Original publication available at: https://doi.org/10.1016/j.jid.2017.11.036 Copyright: Elsevier http://www.elsevier.com/ Genome-Wide DNA Methylation Profiling Identifies Differential Methylation in Uninvolved Psoriatic Epidermis Deepti Verma*a, Anna-Karin Ekman*a, Cecilia Bivik Edinga and Charlotta Enerbäcka *Authors contributed equally aIngrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Division of Dermatology, Linköping University, Linköping, Sweden Corresponding author: Charlotta Enerbäck Ingrid Asp Psoriasis Research Center, Department of Clinical and Experimental Medicine, Linköping University SE-581 85 Linköping, Sweden Phone: +46 10 103 7429 E-mail: [email protected] Short title Differential methylation in psoriasis Abbreviations CGI, CpG island; DMS, differentially methylated site; RRBS, reduced representation bisulphite sequencing Keywords (max 6) psoriasis, epidermis, methylation, Wnt, susceptibility, expression 1 ABSTRACT Psoriasis is a chronic inflammatory skin disease with both local and systemic components. Genome-wide approaches have identified more than 60 psoriasis-susceptibility loci, but genes are estimated to explain only one third of the heritability in psoriasis, suggesting additional, yet unidentified, sources of heritability. -
BIOTECHNO 2020 Proceedings
BIOTECHNO 2020 The Twelfth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies ISBN: 978-1-61208-792-4 September 27th – October 1st, 2020 BIOTECHNO 2020 Editors Birgit Gersbeck-Schierholz, Leibniz Universität Hannover, Germany 1 / 34 BIOTECHNO 2020 Forward The Twelfth International Conference on Bioinformatics, Biocomputational Systems and Biotechnologies (BIOTECHNO 2020) continued a series of events covering these three main areas: bioinformatics, biomedical technologies, and biocomputing. Bioinformatics deals with the system-level study of complex interactions in biosystems providing a quantitative systemic approach to understand them and appropriate tool support and concepts to model them. Understanding and modeling biosystems requires simulation of biological behaviors and functions. Bioinformatics itself constitutes a vast area of research and specialization, as many classical domains such as databases, modeling, and regular expressions are used to represent, store, retrieve and process a huge volume of knowledge. Biotechnology is defined as the industrial use of living organisms or biological techniques developed through basic research. Bio-oriented technologies became very popular in various research topics and industrial market segments. Current human mechanisms seem to offer significant ways for improving theories, algorithms, technologies, products and systems. The focus is driven by fundamentals in approaching and applying biotechnologies in terms of engineering methods, special electronics, and special materials and systems. Borrowing simplicity and performance from the real life, biodevices cover a large spectrum of areas, from sensors, chips, and biometry to computing. One of the chief domains is represented by the biomedical biotechnologies, from instrumentation to monitoring, from simple sensors to integrated systems, including image processing and visualization systems. As the state-of-the- art evolves at fast speed, new biotechnologies and biosystems become available. -
Supplementary Table 1: Adhesion Genes Data Set
Supplementary Table 1: Adhesion genes data set PROBE Entrez Gene ID Celera Gene ID Gene_Symbol Gene_Name 160832 1 hCG201364.3 A1BG alpha-1-B glycoprotein 223658 1 hCG201364.3 A1BG alpha-1-B glycoprotein 212988 102 hCG40040.3 ADAM10 ADAM metallopeptidase domain 10 133411 4185 hCG28232.2 ADAM11 ADAM metallopeptidase domain 11 110695 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 195222 8038 hCG40937.4 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 165344 8751 hCG20021.3 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 189065 6868 null ADAM17 ADAM metallopeptidase domain 17 (tumor necrosis factor, alpha, converting enzyme) 108119 8728 hCG15398.4 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 117763 8748 hCG20675.3 ADAM20 ADAM metallopeptidase domain 20 126448 8747 hCG1785634.2 ADAM21 ADAM metallopeptidase domain 21 208981 8747 hCG1785634.2|hCG2042897 ADAM21 ADAM metallopeptidase domain 21 180903 53616 hCG17212.4 ADAM22 ADAM metallopeptidase domain 22 177272 8745 hCG1811623.1 ADAM23 ADAM metallopeptidase domain 23 102384 10863 hCG1818505.1 ADAM28 ADAM metallopeptidase domain 28 119968 11086 hCG1786734.2 ADAM29 ADAM metallopeptidase domain 29 205542 11085 hCG1997196.1 ADAM30 ADAM metallopeptidase domain 30 148417 80332 hCG39255.4 ADAM33 ADAM metallopeptidase domain 33 140492 8756 hCG1789002.2 ADAM7 ADAM metallopeptidase domain 7 122603 101 hCG1816947.1 ADAM8 ADAM metallopeptidase domain 8 183965 8754 hCG1996391 ADAM9 ADAM metallopeptidase domain 9 (meltrin gamma) 129974 27299 hCG15447.3 ADAMDEC1 ADAM-like, -
Cellular and Molecular Signatures in the Disease Tissue of Early
Cellular and Molecular Signatures in the Disease Tissue of Early Rheumatoid Arthritis Stratify Clinical Response to csDMARD-Therapy and Predict Radiographic Progression Frances Humby1,* Myles Lewis1,* Nandhini Ramamoorthi2, Jason Hackney3, Michael Barnes1, Michele Bombardieri1, Francesca Setiadi2, Stephen Kelly1, Fabiola Bene1, Maria di Cicco1, Sudeh Riahi1, Vidalba Rocher-Ros1, Nora Ng1, Ilias Lazorou1, Rebecca E. Hands1, Desiree van der Heijde4, Robert Landewé5, Annette van der Helm-van Mil4, Alberto Cauli6, Iain B. McInnes7, Christopher D. Buckley8, Ernest Choy9, Peter Taylor10, Michael J. Townsend2 & Costantino Pitzalis1 1Centre for Experimental Medicine and Rheumatology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK. Departments of 2Biomarker Discovery OMNI, 3Bioinformatics and Computational Biology, Genentech Research and Early Development, South San Francisco, California 94080 USA 4Department of Rheumatology, Leiden University Medical Center, The Netherlands 5Department of Clinical Immunology & Rheumatology, Amsterdam Rheumatology & Immunology Center, Amsterdam, The Netherlands 6Rheumatology Unit, Department of Medical Sciences, Policlinico of the University of Cagliari, Cagliari, Italy 7Institute of Infection, Immunity and Inflammation, University of Glasgow, Glasgow G12 8TA, UK 8Rheumatology Research Group, Institute of Inflammation and Ageing (IIA), University of Birmingham, Birmingham B15 2WB, UK 9Institute of -
In a Neuroblastoma Patient Disrupts NBPF1, a Novel Putative Tumor
A Constitutional Translocation t(1;17)(p36.2;q11.2) in a Neuroblastoma Patient Disrupts NBPF1 , a novel putative tumor suppressor gene Vanessa Andries , Karl Vandepoele , Katrien Staes, and Frans van Roy Molecular Cell Biology Unit, Dept. for Molecular Biomedical Research, VIB/Ghent University, Technologiepark 927, B-9052 Ghent (Zwijnaarde) E-mail: [email protected], [email protected] Neuroblastoma (NB) is the most common extracranial solid tumor in children and is characterized by a number of recurrent genetic alterations: gain of chromosome 17q, amplification of MYCN , and deletion of 1p36. We found that a constitutional translocation t(1;17)(p36.2;q11.2) in a neuroblastoma patient (Laureys et al., 1995) resulted in the disruption of a novel gene, NBPF1 (Neuroblastoma Breakpoint Family, member 1). This gene is built of repetitive elements and is subject of structural variation in the human population. Thorough analysis of genomic sequences revealed that NBPF1 is a member of a recently expanded gene family, with gene copies located on segmental duplications of chromosome 1 (Vandepoele et al., 2005). Both in silico and in vitro analysis failed to identify any rodent orthologs for the human NBPF genes. The members of the NBPF gene family are widely expressed, both in normal and cancerous tissues, including neuroblastoma cells. Our identification of NBPF-interacting proteins may link these genes to important signalling pathways such as the Wnt and NF-kappaB signalling pathways. The high sequence identity between different NBPF paralogs has thus far disabled the analysis of gene-specific expression patterns, but the development of an NBPF1 -specific qRT-PCR assay is in progress. -
ATA33632-NBPF3 Rabbit Polyclonal Antibody
ATAGENIX LABORATORIES Catalog Number:ATA33632 NBPF3 rabbit Polyclonal Antibody Product overview product name NBPF3 rabbit Polyclonal Antibody catalog No. ATA33632 Category Primary antibodies Host Rabbit Species specificity Human Tested applications WB,ELISA Clonality Polyclonal Conjugation Unconjugated Immunogen Synthesized peptide derived from human protein . at AA range: 410-490 Product performance Form Liquid Storage Use a manual defrost freezer and avoid repeated freeze thaw cycles. Store at 4 °C for frequent use. Store at -20 to -80 °C for twelve months from the date of receipt. Purity The antibody was affinity-purified from rabbit antiserum by affinity-chromatography using epitope-specific immunogen. Dilution range WB 1:500-2000 ELISA 1:5000-20000 Product background neuroblastoma breakpoint family member 3(NBPF3) Homo sapiens This gene is a member of the neuroblastoma breakpoint family (NBPF) which consists of dozens of recently duplicated genes primarily located in segmental duplications on human chromosome 1. This gene family has experienced its greatest expansion within the human lineage and has expanded, to a lesser extent, among primates in general. Members of this gene family are characterized by tandemly repeated copies of DUF1220 protein domains. DUF1220 copy number variations in human chromosomal region 1q21.1, where most DUF1220 domains are located, have been implicated in a number of developmental and neurogenetic diseases such as microcephaly, macrocephaly, autism, schizophrenia, mental retardation, congenital heart disease, neuroblastoma, and congenital kidney and urinary tract anomalies. Altered expression of some gene family members is associated with several types of cancer. This gene fami Web:www.atagenix.com E-mail: [email protected] Tel: 027-87433958. -
Analysis of the Indacaterol-Regulated Transcriptome in Human Airway
Supplemental material to this article can be found at: http://jpet.aspetjournals.org/content/suppl/2018/04/13/jpet.118.249292.DC1 1521-0103/366/1/220–236$35.00 https://doi.org/10.1124/jpet.118.249292 THE JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS J Pharmacol Exp Ther 366:220–236, July 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Analysis of the Indacaterol-Regulated Transcriptome in Human Airway Epithelial Cells Implicates Gene Expression Changes in the s Adverse and Therapeutic Effects of b2-Adrenoceptor Agonists Dong Yan, Omar Hamed, Taruna Joshi,1 Mahmoud M. Mostafa, Kyla C. Jamieson, Radhika Joshi, Robert Newton, and Mark A. Giembycz Departments of Physiology and Pharmacology (D.Y., O.H., T.J., K.C.J., R.J., M.A.G.) and Cell Biology and Anatomy (M.M.M., R.N.), Snyder Institute for Chronic Diseases, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada Received March 22, 2018; accepted April 11, 2018 Downloaded from ABSTRACT The contribution of gene expression changes to the adverse and activity, and positive regulation of neutrophil chemotaxis. The therapeutic effects of b2-adrenoceptor agonists in asthma was general enriched GO term extracellular space was also associ- investigated using human airway epithelial cells as a therapeu- ated with indacaterol-induced genes, and many of those, in- tically relevant target. Operational model-fitting established that cluding CRISPLD2, DMBT1, GAS1, and SOCS3, have putative jpet.aspetjournals.org the long-acting b2-adrenoceptor agonists (LABA) indacaterol, anti-inflammatory, antibacterial, and/or antiviral activity. Numer- salmeterol, formoterol, and picumeterol were full agonists on ous indacaterol-regulated genes were also induced or repressed BEAS-2B cells transfected with a cAMP-response element in BEAS-2B cells and human primary bronchial epithelial cells by reporter but differed in efficacy (indacaterol $ formoterol . -
Appendix 2. Significantly Differentially Regulated Genes in Term Compared with Second Trimester Amniotic Fluid Supernatant
Appendix 2. Significantly Differentially Regulated Genes in Term Compared With Second Trimester Amniotic Fluid Supernatant Fold Change in term vs second trimester Amniotic Affymetrix Duplicate Fluid Probe ID probes Symbol Entrez Gene Name 1019.9 217059_at D MUC7 mucin 7, secreted 424.5 211735_x_at D SFTPC surfactant protein C 416.2 206835_at STATH statherin 363.4 214387_x_at D SFTPC surfactant protein C 295.5 205982_x_at D SFTPC surfactant protein C 288.7 1553454_at RPTN repetin solute carrier family 34 (sodium 251.3 204124_at SLC34A2 phosphate), member 2 238.9 206786_at HTN3 histatin 3 161.5 220191_at GKN1 gastrokine 1 152.7 223678_s_at D SFTPA2 surfactant protein A2 130.9 207430_s_at D MSMB microseminoprotein, beta- 99.0 214199_at SFTPD surfactant protein D major histocompatibility complex, class II, 96.5 210982_s_at D HLA-DRA DR alpha 96.5 221133_s_at D CLDN18 claudin 18 94.4 238222_at GKN2 gastrokine 2 93.7 1557961_s_at D LOC100127983 uncharacterized LOC100127983 93.1 229584_at LRRK2 leucine-rich repeat kinase 2 HOXD cluster antisense RNA 1 (non- 88.6 242042_s_at D HOXD-AS1 protein coding) 86.0 205569_at LAMP3 lysosomal-associated membrane protein 3 85.4 232698_at BPIFB2 BPI fold containing family B, member 2 84.4 205979_at SCGB2A1 secretoglobin, family 2A, member 1 84.3 230469_at RTKN2 rhotekin 2 82.2 204130_at HSD11B2 hydroxysteroid (11-beta) dehydrogenase 2 81.9 222242_s_at KLK5 kallikrein-related peptidase 5 77.0 237281_at AKAP14 A kinase (PRKA) anchor protein 14 76.7 1553602_at MUCL1 mucin-like 1 76.3 216359_at D MUC7 mucin 7,