Session 6. Genomics and Epigenomics Lectures L6.1 L6.2
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Global Analysis of O-Glcnac Glycoproteins in Activated Human T Cells Peder J
Global Analysis of O-GlcNAc Glycoproteins in Activated Human T Cells Peder J. Lund, Joshua E. Elias and Mark M. Davis This information is current as J Immunol 2016; 197:3086-3098; Prepublished online 21 of October 2, 2021. September 2016; doi: 10.4049/jimmunol.1502031 http://www.jimmunol.org/content/197/8/3086 Downloaded from Supplementary http://www.jimmunol.org/content/suppl/2016/09/20/jimmunol.150203 Material 1.DCSupplemental References This article cites 89 articles, 32 of which you can access for free at: http://www.jimmunol.org/content/197/8/3086.full#ref-list-1 http://www.jimmunol.org/ Why The JI? Submit online. • Rapid Reviews! 30 days* from submission to initial decision • No Triage! Every submission reviewed by practicing scientists • Fast Publication! 4 weeks from acceptance to publication by guest on October 2, 2021 *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 Author Choice Freely available online through The Journal of Immunology Author Choice option 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 © 2016 by The American Association of Immunologists, Inc. All rights reserved. Print ISSN: 0022-1767 Online ISSN: 1550-6606. The Journal of Immunology Global Analysis of O-GlcNAc Glycoproteins in Activated Human T Cells Peder J. -
Content Based Search in Gene Expression Databases and a Meta-Analysis of Host Responses to Infection
Content Based Search in Gene Expression Databases and a Meta-analysis of Host Responses to Infection A Thesis Submitted to the Faculty of Drexel University by Francis X. Bell in partial fulfillment of the requirements for the degree of Doctor of Philosophy November 2015 c Copyright 2015 Francis X. Bell. All Rights Reserved. ii Acknowledgments I would like to acknowledge and thank my advisor, Dr. Ahmet Sacan. Without his advice, support, and patience I would not have been able to accomplish all that I have. I would also like to thank my committee members and the Biomed Faculty that have guided me. I would like to give a special thanks for the members of the bioinformatics lab, in particular the members of the Sacan lab: Rehman Qureshi, Daisy Heng Yang, April Chunyu Zhao, and Yiqian Zhou. Thank you for creating a pleasant and friendly environment in the lab. I give the members of my family my sincerest gratitude for all that they have done for me. I cannot begin to repay my parents for their sacrifices. I am eternally grateful for everything they have done. The support of my sisters and their encouragement gave me the strength to persevere to the end. iii Table of Contents LIST OF TABLES.......................................................................... vii LIST OF FIGURES ........................................................................ xiv ABSTRACT ................................................................................ xvii 1. A BRIEF INTRODUCTION TO GENE EXPRESSION............................. 1 1.1 Central Dogma of Molecular Biology........................................... 1 1.1.1 Basic Transfers .......................................................... 1 1.1.2 Uncommon Transfers ................................................... 3 1.2 Gene Expression ................................................................. 4 1.2.1 Estimating Gene Expression ............................................ 4 1.2.2 DNA Microarrays ...................................................... -
Thesis Master Doc Revamp
The impact of Alu elements on the human proteome Sarah Elizabeth Atkinson Submitted in accordance with the requirements for the degree of Doctor of Philosophy The University of Leeds School of Chemistry May 2019 Acknowledgements Acknowledgements Firstly, I would like to thank Prof. Paul Taylor, Dr Michael Webb and Dr Suzanne Dilly for their guidance and support throughout my PhD, as well as the University of Leeds and Valirx Plc for providing me with this wonderful opportunity. Secondly, I would like to extend my deepest thanks to the members of Lab 1.49, past and present, for all the support they have provided throughout my PhD. In particular, I would like to thank Jack Caudwell for providing me with constant moral support and always keeping a smile on my face, as well as helping to provide the warm and social atmosphere that makes working in 1.49 so special. You made my entire PhD experience infinitely more enjoyable! To Ryan, I hope your next desk buddy is more of a pushover and your future desk take overs are more successful than they were with me. Additionally, I would like to thank Pablo, Devón and JoDo for providing me with friendship and support both inside and outside of the university. It is, of course, customary to thank my parents, who have allowed me to remain in debt with the ‘Bank of Mum and Dad’ whilst I have postponed getting a ‘real job’ for as long as physically possible. On a more serious note, they have always provided me with the upmost support and it has never gone unappreciated. -
Functional Classification of 15 Million Snps Detected from Diverse
DNA Research, 2015, 22(3), 205–217 doi: 10.1093/dnares/dsv005 Advance Access Publication Date: 29 April 2015 Full Paper Full Paper Functional classification of 15 million SNPs detected from diverse chicken populations Almas A. Gheyas*, Clarissa Boschiero†, Lel Eory, Hannah Ralph, Richard Kuo, John A. Woolliams, and David W. Burt* The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK *To whom correspondence should be addressed. Tel. +44 (0)131-651-9216. Fax. +44 (0)131-651-9105. E-mail: dave.burt@roslin. ed.ac.uk (D.W.B.); Tel. +44(0)131-651-9100. Fax. +44(0)131-651-9105. E-mail: [email protected] (A.A.G.) †Current Address: USP/ESALQ, Dept. de Zootecnia, Piracicaba, SP 13418-900, Brazil. Edited by Dr Toshihiko Shiroishi Received 30 January 2015; Accepted 20 March 2015 Abstract Next-generation sequencing has prompted a surge of discovery of millions of genetic variants from vertebrate genomes. Besides applications in genetic association and linkage studies, a fraction of these variants will have functional consequences. This study describes detection and characteriza- tion of 15 million SNPs from chicken genome with the goal to predict variants with potential function- al implications (pfVars) from both coding and non-coding regions. The study reports: 183K amino acid-altering SNPs of which 48% predicted as evolutionary intolerant, 13K splicing variants, 51K like- ly to alter RNA secondary structures, 500K within most conserved elements and 3K from non-coding RNAs. Regions of local fixation within commercial broiler and layer lines were investigated as poten- tial selective sweeps using genome-wide SNP data. -
Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations Fall 2010 Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Renuka Nayak University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Computational Biology Commons, and the Genomics Commons Recommended Citation Nayak, Renuka, "Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress" (2010). Publicly Accessible Penn Dissertations. 1559. https://repository.upenn.edu/edissertations/1559 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/1559 For more information, please contact [email protected]. Coexpression Networks Based on Natural Variation in Human Gene Expression at Baseline and Under Stress Abstract Genes interact in networks to orchestrate cellular processes. Here, we used coexpression networks based on natural variation in gene expression to study the functions and interactions of human genes. We asked how these networks change in response to stress. First, we studied human coexpression networks at baseline. We constructed networks by identifying correlations in expression levels of 8.9 million gene pairs in immortalized B cells from 295 individuals comprising three independent samples. The resulting networks allowed us to infer interactions between biological processes. We used the network to predict the functions of poorly-characterized human genes, and provided some experimental support. Examining genes implicated in disease, we found that IFIH1, a diabetes susceptibility gene, interacts with YES1, which affects glucose transport. Genes predisposing to the same diseases are clustered non-randomly in the network, suggesting that the network may be used to identify candidate genes that influence disease susceptibility. -
Universidad Autónoma De Madrid
Universidad Autónoma de Madrid Departamento de Bioquímica Identification of the substrates of the protease MT1-MMP in TNFα- stimulated endothelial cells by quantitative proteomics. Analysis of their potential use as biomarkers in inflammatory bowel disease. Agnieszka A. Koziol Tesis doctoral Madrid, 2013 2 Departamento de Bioquímica Facultad de Medicina Universidad Autónoma de Madrid Identification of the substrates of the protease MT1-MMP in TNFα- stimulated endothelial cells by quantitative proteomics. Analysis of their potential use as biomarkers in inflammatory bowel disease. Memoria presentada por Agnieszka A. Koziol licenciada en Ciencias Biológicas para optar al grado de Doctor. Directora: Dra Alicia García Arroyo Centro Nacional de Investigaciones Cardiovasculares (CNIC) Madrid, 2013 3 4 ACKNOWLEDGEMENTS - ACKNOWLEDGEMENTS - First and foremost I would like to express my sincere gratitude to my supervisor Dr. Alicia García Arroyo for giving me the great opportunity to study under her direction. Her encouragement, guidance and support from the beginning to the end, enabled me to develop and understand the subject. Her feedback to this manuscript, critical reading and corrections was inappreciable to finish this dissertation. Next, I would like to express my gratitude to those who helped me substantially along the way. To all members of MMPs’ lab, for their interest in the project, teaching me during al these years and valuable contribution at the seminary discussion. Without your help it would have not been possible to do some of those experiments. Thank you all for creating a nice atmosphere at work and for being so good friends in private. I would like to also thank all of the collaborators and technical units for their support and professionalism. -
Proteogenomic Single Cell Analysis of Skeletal Muscle Myocytes 1 2 Katherine M. Fomchenko1,4, Rohan X. Verma1,4, Suraj Kannan2
bioRxiv preprint doi: https://doi.org/10.1101/2020.01.23.916791; this version posted January 24, 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 4.0 International license. 1 Proteogenomic single cell analysis of skeletal muscle myocytes 2 3 Katherine M. Fomchenko1,4, Rohan X. Verma1,4, Suraj Kannan2, Brian L. Lin2, Xiaoping Yang1, 4 Tim O. Nieuwenhuis1, Arun H. Patil1, Karen Fox-Talbot1, Matthew N. McCall3, Chulan Kwon2, 5 David A. Kass2, Avi Z. Rosenberg1, Marc K. Halushka1* 6 7 1 Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA 8 2 Division of Cardiology, Department of Medicine, Johns Hopkins University School of 9 Medicine, Baltimore, MD, USA 10 3 Department of Biostatistics and Computational Biology, University of Rochester Medical 11 Center, Rochester, NY, USA 12 4 These authors contributed equally to this project 13 14 Email Addresses: 15 [email protected] 16 [email protected] 17 [email protected] 18 [email protected] 19 [email protected] 20 [email protected] 21 [email protected] 22 [email protected] 23 [email protected] 24 [email protected] 25 [email protected] 26 [email protected] 27 [email protected] 28 29 * Correspondence and address for reprints to: 30 Marc K. Halushka, M.D., Ph.D. 31 Johns Hopkins University School of Medicine 32 Ross Bldg. Rm 632B 33 720 Rutland Avenue 34 Baltimore, MD 21205 35 410-614-8138 (ph) 36 410-502-5862 (fax) 37 [email protected] 38 bioRxiv preprint doi: https://doi.org/10.1101/2020.01.23.916791; this version posted January 24, 2020. -
DNA Methylation Signature of Human Hippocampus in Alzheimer's
Altuna et al. Clinical Epigenetics (2019) 11:91 https://doi.org/10.1186/s13148-019-0672-7 RESEARCH Open Access DNA methylation signature of human hippocampus in Alzheimer’s disease is linked to neurogenesis Miren Altuna1,2, Amaya Urdánoz-Casado1, Javier Sánchez-Ruiz de Gordoa1,2, María V. Zelaya3, Alberto Labarga4, Julie M. J. Lepesant5, Miren Roldán1, Idoia Blanco-Luquin1, Álvaro Perdones4, Rosa Larumbe1,2, Ivonne Jericó2, Carmen Echavarri1,2, Iván Méndez-López1,6, Luisa Di Stefano5 and Maite Mendioroz1,2* Abstract Background: Drawing the epigenome landscape of Alzheimer’s disease (AD) still remains a challenge. To characterize the epigenetic molecular basis of the human hippocampus in AD, we profiled genome-wide DNA methylation levels in hippocampal samples from a cohort of pure AD patients and controls by using the Illumina 450K methylation arrays. Results: Up to 118 AD-related differentially methylated positions (DMPs) were identified in the AD hippocampus, and extended mapping of specific regions was obtained by bisulfite cloning sequencing. AD-related DMPs were significantly correlated with phosphorylated tau burden. Functional analysis highlighted that AD-related DMPs were enriched in poised promoters that were not generally maintained in committed neural progenitor cells, as shown by ChiP-qPCR experiments. Interestingly, AD-related DMPs preferentially involved neurodevelopmental and neurogenesis- related genes. Finally, InterPro ontology analysis revealed enrichment in homeobox-containing transcription factors in the set of AD-related DMPs. Conclusions: These results suggest that altered DNA methylation in the AD hippocampus occurs at specific regulatory regions crucial for neural differentiation supporting the notion that adult hippocampal neurogenesis may play a role in AD through epigenetic mechanisms. -
DNA Res-2015-Gheyas-Dnares-Dsv005
Edinburgh Research Explorer Functional classification of 15 million SNPs detected from diverse chicken populations Citation for published version: Gheyas, AA, Boschiero, C, Eory, L, Ralph, H, Kuo, R, Woolliams, JA & Burt, DW 2015, 'Functional classification of 15 million SNPs detected from diverse chicken populations', DNA Research, vol. 22, no. 3, pp. 205-217. https://doi.org/10.1093/dnares/dsv005 Digital Object Identifier (DOI): 10.1093/dnares/dsv005 Link: Link to publication record in Edinburgh Research Explorer Document Version: Publisher's PDF, also known as Version of record Published In: DNA Research General rights Copyright for the publications made accessible via the Edinburgh Research Explorer is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The University of Edinburgh has made every reasonable effort to ensure that Edinburgh Research Explorer content complies with UK legislation. If you believe that the public display of this file breaches copyright please contact [email protected] providing details, and we will remove access to the work immediately and investigate your claim. Download date: 28. Sep. 2021 DNA Research Advance Access published April 29, 2015 DNA Research, 2015, 1–13 doi: 10.1093/dnares/dsv005 Full Paper Full Paper Functional classification of 15 million SNPs detected from diverse chicken populations Almas A. Gheyas*, Clarissa Boschiero†, Lel Eory, Hannah Ralph, Richard Kuo, John A. Woolliams, and David W. Burt* The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Easter Bush Campus, Downloaded from Midlothian EH25 9RG, UK *To whom correspondence should be addressed.