Affymetrix Probe ID Gene Symbol 1007 S at DDR1 1494 F At
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach
Mafalda Rita Avó Bacalhau Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach Tese de doutoramento do Programa de Doutoramento em Ciências da Saúde, ramo de Ciências Biomédicas, orientada pela Professora Doutora Maria Manuela Monteiro Grazina e co-orientada pelo Professor Doutor Henrique Manuel Paixão dos Santos Girão e pela Professora Doutora Lee-Jun C. Wong e apresentada à Faculdade de Medicina da Universidade de Coimbra Julho 2017 Faculty of Medicine Establishing the pathogenicity of novel mitochondrial DNA sequence variations: a cell and molecular biology approach Mafalda Rita Avó Bacalhau Tese de doutoramento do programa em Ciências da Saúde, ramo de Ciências Biomédicas, realizada sob a orientação científica da Professora Doutora Maria Manuela Monteiro Grazina; e co-orientação do Professor Doutor Henrique Manuel Paixão dos Santos Girão e da Professora Doutora Lee-Jun C. Wong, apresentada à Faculdade de Medicina da Universidade de Coimbra. Julho, 2017 Copyright© Mafalda Bacalhau e Manuela Grazina, 2017 Esta cópia da tese é fornecida na condição de que quem a consulta reconhece que os direitos de autor são pertença do autor da tese e do orientador científico e que nenhuma citação ou informação obtida a partir dela pode ser publicada sem a referência apropriada e autorização. This copy of the thesis has been supplied on the condition that anyone who consults it recognizes that its copyright belongs to its author and scientific supervisor and that no quotation from the -
A Novel Approach to Identify Driver Genes Involved in Androgen-Independent Prostate Cancer
Schinke et al. Molecular Cancer 2014, 13:120 http://www.molecular-cancer.com/content/13/1/120 RESEARCH Open Access A novel approach to identify driver genes involved in androgen-independent prostate cancer Ellyn N Schinke1, Victor Bii1, Arun Nalla1, Dustin T Rae1, Laura Tedrick1, Gary G Meadows1 and Grant D Trobridge1,2* Abstract Background: Insertional mutagenesis screens have been used with great success to identify oncogenes and tumor suppressor genes. Typically, these screens use gammaretroviruses (γRV) or transposons as insertional mutagens. However, insertional mutations from replication-competent γRVs or transposons that occur later during oncogenesis can produce passenger mutations that do not drive cancer progression. Here, we utilized a replication-incompetent lentiviral vector (LV) to perform an insertional mutagenesis screen to identify genes in the progression to androgen-independent prostate cancer (AIPC). Methods: Prostate cancer cells were mutagenized with a LV to enrich for clones with a selective advantage in an androgen-deficient environment provided by a dysregulated gene(s) near the vector integration site. We performed our screen using an in vitro AIPC model and also an in vivo xenotransplant model for AIPC. Our approach identified proviral integration sites utilizing a shuttle vector that allows for rapid rescue of plasmids in E. coli that contain LV long terminal repeat (LTR)-chromosome junctions. This shuttle vector approach does not require PCR amplification and has several advantages over PCR-based techniques. Results: Proviral integrations were enriched near prostate cancer susceptibility loci in cells grown in androgen- deficient medium (p < 0.001), and five candidate genes that influence AIPC were identified; ATPAF1, GCOM1, MEX3D, PTRF, and TRPM4. -
Efficacy and Mechanistic Evaluation of Tic10, a Novel Antitumor Agent
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2012 Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Joshua Edward Allen University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Oncology Commons Recommended Citation Allen, Joshua Edward, "Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent" (2012). Publicly Accessible Penn Dissertations. 488. https://repository.upenn.edu/edissertations/488 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/488 For more information, please contact [email protected]. Efficacy and Mechanisticv E aluation of Tic10, A Novel Antitumor Agent Abstract TNF-related apoptosis-inducing ligand (TRAIL; Apo2L) is an endogenous protein that selectively induces apoptosis in cancer cells and is a critical effector in the immune surveillance of cancer. Recombinant TRAIL and TRAIL-agonist antibodies are in clinical trials for the treatment of solid malignancies due to the cancer-specific cytotoxicity of TRAIL. Recombinant TRAIL has a short serum half-life and both recombinant TRAIL and TRAIL receptor agonist antibodies have a limited capacity to perfuse to tissue compartments such as the brain, limiting their efficacy in certain malignancies. To overcome such limitations, we searched for small molecules capable of inducing the TRAIL gene using a high throughput luciferase reporter gene assay. We selected TRAIL-inducing compound 10 (TIC10) for further study based on its induction of TRAIL at the cell surface and its promising therapeutic index. TIC10 is a potent, stable, and orally active antitumor agent that crosses the blood-brain barrier and transcriptionally induces TRAIL and TRAIL-mediated cell death in a p53-independent manner. -
Roles of the CSE1L-Mediated Nuclear Import Pathway in Epigenetic
Roles of the CSE1L-mediated nuclear import pathway PNAS PLUS in epigenetic silencing Qiang Donga,b,c, Xiang Lia,b,c, Cheng-Zhi Wangb, Shaohua Xuc, Gang Yuanc, Wei Shaoc, Baodong Liud, Yong Zhengb, Hailin Wangd, Xiaoguang Leic,e,f, Zhuqiang Zhangb,1, and Bing Zhua,b,g,1 aGraduate Program, Peking Union Medical College and Chinese Academy of Medical Sciences, 100730 Beijing, China; bNational Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101 Beijing, China; cNational Institute of Biological Sciences, 102206 Beijing, China; dThe State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, 100085 Beijing, China; eBeijing National Laboratory for Molecular Sciences, Department of Chemical Biology, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China; fPeking-Tsinghua Center for Life Sciences, Peking University, 100871 Beijing, China; and gCollege of Life Sciences, University of Chinese Academy of Sciences, 100049 Beijing, China Edited by Arthur D. Riggs, Beckman Research Institute of City of Hope, Duarte, CA, and approved March 21, 2018 (received for review January 17, 2018) Epigenetic silencing can be mediated by various mechanisms, CSE1L, a key player in the nuclear import pathway, as an es- and many regulators remain to be identified. Here, we report a sential factor for maintaining the repression of many methyl- genome-wide siRNA screening to identify regulators essential for ated genes. Mechanistically, CSE1L functions by facilitating maintaining gene repression of a CMV promoter silenced by DNA the nuclear import of certain cargo proteins that are essential methylation. -
Supplemental Table S1
Entrez Gene Symbol Gene Name Affymetrix EST Glomchip SAGE Stanford Literature HPA confirmed Gene ID Profiling profiling Profiling Profiling array profiling confirmed 1 2 A2M alpha-2-macroglobulin 0 0 0 1 0 2 10347 ABCA7 ATP-binding cassette, sub-family A (ABC1), member 7 1 0 0 0 0 3 10350 ABCA9 ATP-binding cassette, sub-family A (ABC1), member 9 1 0 0 0 0 4 10057 ABCC5 ATP-binding cassette, sub-family C (CFTR/MRP), member 5 1 0 0 0 0 5 10060 ABCC9 ATP-binding cassette, sub-family C (CFTR/MRP), member 9 1 0 0 0 0 6 79575 ABHD8 abhydrolase domain containing 8 1 0 0 0 0 7 51225 ABI3 ABI gene family, member 3 1 0 1 0 0 8 29 ABR active BCR-related gene 1 0 0 0 0 9 25841 ABTB2 ankyrin repeat and BTB (POZ) domain containing 2 1 0 1 0 0 10 30 ACAA1 acetyl-Coenzyme A acyltransferase 1 (peroxisomal 3-oxoacyl-Coenzyme A thiol 0 1 0 0 0 11 43 ACHE acetylcholinesterase (Yt blood group) 1 0 0 0 0 12 58 ACTA1 actin, alpha 1, skeletal muscle 0 1 0 0 0 13 60 ACTB actin, beta 01000 1 14 71 ACTG1 actin, gamma 1 0 1 0 0 0 15 81 ACTN4 actinin, alpha 4 0 0 1 1 1 10700177 16 10096 ACTR3 ARP3 actin-related protein 3 homolog (yeast) 0 1 0 0 0 17 94 ACVRL1 activin A receptor type II-like 1 1 0 1 0 0 18 8038 ADAM12 ADAM metallopeptidase domain 12 (meltrin alpha) 1 0 0 0 0 19 8751 ADAM15 ADAM metallopeptidase domain 15 (metargidin) 1 0 0 0 0 20 8728 ADAM19 ADAM metallopeptidase domain 19 (meltrin beta) 1 0 0 0 0 21 81792 ADAMTS12 ADAM metallopeptidase with thrombospondin type 1 motif, 12 1 0 0 0 0 22 9507 ADAMTS4 ADAM metallopeptidase with thrombospondin type 1 -
Seq2pathway Vignette
seq2pathway Vignette Bin Wang, Xinan Holly Yang, Arjun Kinstlick May 19, 2021 Contents 1 Abstract 1 2 Package Installation 2 3 runseq2pathway 2 4 Two main functions 3 4.1 seq2gene . .3 4.1.1 seq2gene flowchart . .3 4.1.2 runseq2gene inputs/parameters . .5 4.1.3 runseq2gene outputs . .8 4.2 gene2pathway . 10 4.2.1 gene2pathway flowchart . 11 4.2.2 gene2pathway test inputs/parameters . 11 4.2.3 gene2pathway test outputs . 12 5 Examples 13 5.1 ChIP-seq data analysis . 13 5.1.1 Map ChIP-seq enriched peaks to genes using runseq2gene .................... 13 5.1.2 Discover enriched GO terms using gene2pathway_test with gene scores . 15 5.1.3 Discover enriched GO terms using Fisher's Exact test without gene scores . 17 5.1.4 Add description for genes . 20 5.2 RNA-seq data analysis . 20 6 R environment session 23 1 Abstract Seq2pathway is a novel computational tool to analyze functional gene-sets (including signaling pathways) using variable next-generation sequencing data[1]. Integral to this tool are the \seq2gene" and \gene2pathway" components in series that infer a quantitative pathway-level profile for each sample. The seq2gene function assigns phenotype-associated significance of genomic regions to gene-level scores, where the significance could be p-values of SNPs or point mutations, protein-binding affinity, or transcriptional expression level. The seq2gene function has the feasibility to assign non-exon regions to a range of neighboring genes besides the nearest one, thus facilitating the study of functional non-coding elements[2]. Then the gene2pathway summarizes gene-level measurements to pathway-level scores, comparing the quantity of significance for gene members within a pathway with those outside a pathway. -
ANKRD11 Gene Ankyrin Repeat Domain 11
ANKRD11 gene ankyrin repeat domain 11 Normal Function The ANKRD11 gene provides instructions for making a protein called ankyrin repeat domain 11 (ANKRD11). As its name suggests, this protein contains multiple regions called ankyrin domains; proteins with these domains help other proteins interact with each other. The ANKRD11 protein interacts with certain proteins called histone deacetylases, which are important for controlling gene activity. Through these interactions, ANKRD11 affects when genes are turned on and off. For example, ANKRD11 brings together histone deacetylases and other proteins called p160 coactivators. This association regulates the ability of p160 coactivators to turn on gene activity. ANKRD11 may also enhance the activity of a protein called p53, which controls the growth and division (proliferation) and the self-destruction (apoptosis) of cells. The ANKRD11 protein is found in nerve cells (neurons) in the brain. During embryonic development, ANKRD11 helps regulate the proliferation of these cells and development of the brain. Researchers speculate that the protein may also be involved in the ability of neurons to change and adapt over time (plasticity), which is important for learning and memory. ANKRD11 may function in other cells in the body and appears to be involved in normal bone development. Health Conditions Related to Genetic Changes KBG syndrome Several ANKRD11 gene mutations have been found to cause KBG syndrome, a condition characterized by large upper front teeth and other unusual facial features, skeletal abnormalities, and intellectual disability. Most of these mutations lead to an abnormally short ANKRD11 protein, which likely has little or no function. Reduction of this protein's function is thought to underlie the signs and symptoms of the condition. -
Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony
Supplementary Data Th2 and non-Th2 molecular phenotypes of asthma using sputum transcriptomics in UBIOPRED Chih-Hsi Scott Kuo1.2, Stelios Pavlidis3, Matthew Loza3, Fred Baribaud3, Anthony Rowe3, Iaonnis Pandis2, Ana Sousa4, Julie Corfield5, Ratko Djukanovic6, Rene 7 7 8 2 1† Lutter , Peter J. Sterk , Charles Auffray , Yike Guo , Ian M. Adcock & Kian Fan 1†* # Chung on behalf of the U-BIOPRED consortium project team 1Airways Disease, National Heart & Lung Institute, Imperial College London, & Biomedical Research Unit, Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, United Kingdom; 2Department of Computing & Data Science Institute, Imperial College London, United Kingdom; 3Janssen Research and Development, High Wycombe, Buckinghamshire, United Kingdom; 4Respiratory Therapeutic Unit, GSK, Stockley Park, United Kingdom; 5AstraZeneca R&D Molndal, Sweden and Areteva R&D, Nottingham, United Kingdom; 6Faculty of Medicine, Southampton University, Southampton, United Kingdom; 7Faculty of Medicine, University of Amsterdam, Amsterdam, Netherlands; 8European Institute for Systems Biology and Medicine, CNRS-ENS-UCBL, Université de Lyon, France. †Contributed equally #Consortium project team members are listed under Supplementary 1 Materials *To whom correspondence should be addressed: [email protected] 2 List of the U-BIOPRED Consortium project team members Uruj Hoda & Christos Rossios, Airways Disease, National Heart & Lung Institute, Imperial College London, UK & Biomedical Research Unit, Biomedical Research Unit, Royal -
3 Cleavage Products of Notch 2/Site and Myelopoiesis by Dysregulating
ADAM10 Overexpression Shifts Lympho- and Myelopoiesis by Dysregulating Site 2/Site 3 Cleavage Products of Notch This information is current as David R. Gibb, Sheinei J. Saleem, Dae-Joong Kang, Mark of October 4, 2021. A. Subler and Daniel H. Conrad J Immunol 2011; 186:4244-4252; Prepublished online 2 March 2011; doi: 10.4049/jimmunol.1003318 http://www.jimmunol.org/content/186/7/4244 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2011/03/02/jimmunol.100331 Material 8.DC1 http://www.jimmunol.org/ References This article cites 45 articles, 16 of which you can access for free at: http://www.jimmunol.org/content/186/7/4244.full#ref-list-1 Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists by guest on October 4, 2021 • Fast Publication! 4 weeks from acceptance to publication *average Subscription Information about subscribing to The Journal of Immunology is online at: http://jimmunol.org/subscription Permissions Submit copyright permission requests at: http://www.aai.org/About/Publications/JI/copyright.html Email Alerts Receive free email-alerts when new articles cite this article. Sign up at: http://jimmunol.org/alerts The Journal of Immunology is published twice each month by The American Association of Immunologists, Inc., 1451 Rockville Pike, Suite 650, Rockville, MD 20852 Copyright © 2011 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology ADAM10 Overexpression Shifts Lympho- and Myelopoiesis by Dysregulating Site 2/Site 3 Cleavage Products of Notch David R. -
The Endocytic Membrane Trafficking Pathway Plays a Major Role
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by University of Liverpool Repository RESEARCH ARTICLE The Endocytic Membrane Trafficking Pathway Plays a Major Role in the Risk of Parkinson’s Disease Sara Bandres-Ciga, PhD,1,2 Sara Saez-Atienzar, PhD,3 Luis Bonet-Ponce, PhD,4 Kimberley Billingsley, MSc,1,5,6 Dan Vitale, MSc,7 Cornelis Blauwendraat, PhD,1 Jesse Raphael Gibbs, PhD,7 Lasse Pihlstrøm, MD, PhD,8 Ziv Gan-Or, MD, PhD,9,10 The International Parkinson’s Disease Genomics Consortium (IPDGC), Mark R. Cookson, PhD,4 Mike A. Nalls, PhD,1,11 and Andrew B. Singleton, PhD1* 1Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA 2Instituto de Investigación Biosanitaria de Granada (ibs.GRANADA), Granada, Spain 3Transgenics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA 4Cell Biology and Gene Expression Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA 5Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom 6Department of Pathophysiology, University of Tartu, Tartu, Estonia 7Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA 8Department of Neurology, Oslo University Hospital, Oslo, Norway 9Department of Neurology and Neurosurgery, Department of Human Genetics, McGill University, Montréal, Quebec, Canada 10Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, Quebec, Canada 11Data Tecnica International, Glen Echo, Maryland, USA ABSTRACT studies, summary-data based Mendelian randomization Background: PD is a complex polygenic disorder. -
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. -
Primate Specific Retrotransposons, Svas, in the Evolution of Networks That Alter Brain Function
Title: Primate specific retrotransposons, SVAs, in the evolution of networks that alter brain function. Olga Vasieva1*, Sultan Cetiner1, Abigail Savage2, Gerald G. Schumann3, Vivien J Bubb2, John P Quinn2*, 1 Institute of Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, U.K 2 Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK 3 Division of Medical Biotechnology, Paul-Ehrlich-Institut, Langen, D-63225 Germany *. Corresponding author Olga Vasieva: Institute of Integrative Biology, Department of Comparative genomics, University of Liverpool, Liverpool, L69 7ZB, [email protected] ; Tel: (+44) 151 795 4456; FAX:(+44) 151 795 4406 John Quinn: Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, The University of Liverpool, Liverpool L69 3BX, UK, [email protected]; Tel: (+44) 151 794 5498. Key words: SVA, trans-mobilisation, behaviour, brain, evolution, psychiatric disorders 1 Abstract The hominid-specific non-LTR retrotransposon termed SINE–VNTR–Alu (SVA) is the youngest of the transposable elements in the human genome. The propagation of the most ancient SVA type A took place about 13.5 Myrs ago, and the youngest SVA types appeared in the human genome after the chimpanzee divergence. Functional enrichment analysis of genes associated with SVA insertions demonstrated their strong link to multiple ontological categories attributed to brain function and the disorders. SVA types that expanded their presence in the human genome at different stages of hominoid life history were also associated with progressively evolving behavioural features that indicated a potential impact of SVA propagation on a cognitive ability of a modern human.