Ectopic Protein Interactions Within BRD4–Chromatin Complexes Drive
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Tepzz 8Z6z54a T
(19) TZZ ZZ_T (11) EP 2 806 054 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 26.11.2014 Bulletin 2014/48 C40B 40/06 (2006.01) C12Q 1/68 (2006.01) C40B 30/04 (2006.01) C07H 21/00 (2006.01) (21) Application number: 14175049.7 (22) Date of filing: 28.05.2009 (84) Designated Contracting States: (74) Representative: Irvine, Jonquil Claire AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HGF Limited HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL 140 London Wall PT RO SE SI SK TR London EC2Y 5DN (GB) (30) Priority: 28.05.2008 US 56827 P Remarks: •Thecomplete document including Reference Tables (62) Document number(s) of the earlier application(s) in and the Sequence Listing can be downloaded from accordance with Art. 76 EPC: the EPO website 09753364.0 / 2 291 553 •This application was filed on 30-06-2014 as a divisional application to the application mentioned (71) Applicant: Genomedx Biosciences Inc. under INID code 62. Vancouver, British Columbia V6J 1J8 (CA) •Claims filed after the date of filing of the application/ after the date of receipt of the divisional application (72) Inventor: Davicioni, Elai R.68(4) EPC). Vancouver British Columbia V6J 1J8 (CA) (54) Systems and methods for expression- based discrimination of distinct clinical disease states in prostate cancer (57) A system for expression-based discrimination of distinct clinical disease states in prostate cancer is provided that is based on the identification of sets of gene transcripts, which are characterized in that changes in expression of each gene transcript within a set of gene transcripts can be correlated with recurrent or non- recur- rent prostate cancer. -
Supplemental Materials and Methods Page
1 2 Supplementary Information for 3 4 5 Vertebrate adaptive radiation is assembled from an ancient and disjunct spatiotemporal 6 landscape 7 8 Emilie J. Richards, Joseph A. McGirr, Jeremy R. Wang, Michelle E. St. John, Jelmer W. 9 Poelstra, Maria J. Solano, Delaney C. O’Connell, Bruce J. Turner, Christopher H. Martin* 10 11 *Correspondence to: [email protected] 12 13 14 15 This PDF file includes: 16 17 Supplementary text 18 Figures S1 to S17 19 Tables S1 to S19 20 SI References 21 22 Other supplementary materials for this manuscript include the following: 23 24 Datasets S1 to S9 25 26 27 28 29 30 31 32 33 34 35 36 37 1 38 Table of Contents 1. Supplemental Materials and Methods Page 1.1 Sampling 4 1.2 Genomic Library Prep 5 1.3 De novo genome assembly and annotation 5 1.4 Population genotyping. 6 1.5 Population genetic analyses 8 1.6 Mutation rate estimation. 10 1.7 Demographic Inferences 12 1.8 Introgression in SSI specialists 13 1.9 Search for candidate adaptive alleles in SSI specialists 15 1.10 Introgression in outgroup generalist populations 18 1.11. Characterization of adaptive alleles through GO analysis 19 1.12 Characterization of adaptive alleles through genome-wide association mapping 19 1.13 Characterization of adaptive alleles through differential gene expression and QTL 22 analysis from previous studies 1.14 Timing of divergence among adaptive alleles 23 1.15 Timing of selective sweeps on adaptive alleles 26 2. Supplementary Results and Discussion 31 2 2.1 Spatiotemporal stages of adaption based on timing of divergence among adaptive alleles 31 2.2 Spatiotemporal stages of adaptation based on timing of selection on adaptive alleles 35 3. -
A Large Multi-Ethnic Genome-Wide Association Study of Adult Body Mass Index Identifies
Genetics: Early Online, published on August 14, 2018 as 10.1534/genetics.118.301479 1 A large multi-ethnic genome-wide association study of adult body mass index identifies 2 novel loci 3 4 Thomas J Hoffmann*,†,1, Hélène Choquet‡, Jie Yin‡, Yambazi Banda*, Mark N Kvale*, 5 Maria Glymour†, Catherine Schaefer‡, Neil Risch*,†,‡, and Eric Jorgenson‡,1 6 7 *Institute for Human Genetics, University of California San Francisco, San Francisco, 8 CA, 94143 9 †Department of Epidemiology and Biostatistics, University of California San Francisco, 10 San Francisco, CA 94158 11 ‡Division of Research, Kaiser Permanente, Northern California, Oakland, CA 94612 12 13 GO Project IRB: CN-09CScha-06-H. 14 15 1 Copyright 2018. 16 Short running title: GWAS of BMI 17 18 Keywords: adult body mass index; adult BMI; genome-wide association study; obesity 19 20 1Corresponding authors: Eric Jorgenson, Division of Research, Kaiser Permanente, 21 Northern California, 2000 Broadway, Oakland, CA 94612, Tel: 510-891-3473, e-mail: 22 [email protected], or Thomas J. Hoffmann, University of California San Francisco, 23 513 Parnassus Ave, San Francisco, CA 94117, Tel: 415-476-2475, e-mail: 24 [email protected]. 25 2 26 Abstract 27 Body mass index (BMI), a proxy measure for obesity, is determined by both 28 environmental (including ethnicity, age, and sex) and genetic factors with over 400 BMI- 29 associated loci identified to date. However, the impact, interplay, and underlying 30 biological mechanisms among BMI, environment, genetics, and ancestry are not 31 completely understood. To further examine these relationships, we utilized 427,509 32 calendar-year averaged BMI measurements on 100,418 adults from the single large 33 multi-ethnic Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. -
WO 2014/172046 A9 O
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) CORRECTED VERSION (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date WO 2014/172046 A9 23 October 2014 (23.10.2014) P C T (51) International Patent Classification: 61/824,253 16 May 2013 (16.05.2013) US C12Q 1/68 (2006.01) G06F 19/20 (201 1.01) 61/860,1 15 30 July 201 3 (30.07.2013) US 61/907,939 22 November 2013 (22. 11.2013) us (21) International Application Number: 61/915,392 12 December 2013 (12. 12.2013) us PCT/US2014/029592 61/935,650 4 February 2014 (04.02.2014) us (22) International Filing Date: 61/940,226 14 February 2014 (14.02.2014) us 14 March 2014 (14.03.2014) (71) Applicant: LIFE TECHNOLOGIES CORPORATION (25) Filing Language: English [US/US]; Legal Department, Intellectual Property, 5791 Van Allen Way, Carlsbad, California 92008 (US). (26) Publication Language: English (72) Inventors: RHODES, Daniel; Life Technologies Corpora (30) Priority Data: tion, Legal Department, Intellectual Property, 5791 Van 61/813,182 17 April 2013 (17.04.2013) Allen Way, Carlsbad, California 92008 (US). SADIS, 61/813,465 18 April 2013 (18.04.2013) Seth; Life Technologies Corporation, Legal Department, [Continued on nextpage] (54) Title: GENE FUSIONS AND GENE VARIANTS ASSOCIATED WITH CANCER (57) Abstract: The disclosure provides gene fusions, gene variants, and novel as sociations with disease states, as well as kits, probes, and methods of using the same. raw cells Annotate and Filter Fusions 424K annotated fusion cells Summarize and Prioritize Fusions Gene Fusion RNASeq data < processing workflow o w o 2014/172046 A 9 1I II II I III IIII II 11lll l ll III! Ill III II Intellectual Property, 5791 Van Allen Way, Carlsbad, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, California 92008 (US). -
A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci
| INVESTIGATION A Large Multiethnic Genome-Wide Association Study of Adult Body Mass Index Identifies Novel Loci Thomas J. Hoffmann,*,†,1 Hélène Choquet,‡ Jie Yin,‡ Yambazi Banda,* Mark N. Kvale,* Maria Glymour,† Catherine Schaefer,‡ Neil Risch,*,†,‡ and Eric Jorgenson‡,1 *Institute for Human Genetics, University of California San Francisco, California 94143, †Department of Epidemiology and Biostatistics, University of California San Francisco, California 94158, and ‡Division of Research, Kaiser Permanente Northern California, Oakland, California 94612 ORCID ID: 0000-0001-9839-8667 (H.C.) ABSTRACT Body mass index (BMI), a proxy measure for obesity, is determined by both environmental (including ethnicity, age, and sex) and genetic factors, with . 400 BMI-associated loci identified to date. However, the impact, interplay, and underlying biological mechanisms among BMI, environment, genetics, and ancestry are not completely understood. To further examine these relationships, we utilized 427,509 calendar year-averaged BMI measurements from 100,418 adults from the single large multiethnic Genetic Epide- miology Research on Adult Health and Aging (GERA) cohort. We observed substantial independent ancestry and nationality differences, including ancestry principal component interactions and nonlinear effects. To increase the list of BMI-associated variants before assessing other differences, we conducted a genome-wide association study (GWAS) in GERA, with replication in the Genetic Investigation of Anthropomorphic Traits (GIANT) consortium combined with the UK Biobank (UKB), followed by GWAS in GERA combined with GIANT, with replication in the UKB. We discovered 30 novel independent BMI loci (P , 5.0 3 1028) that replicated. We then assessed the proportion of BMI variance explained by sex in the UKB using previously identified loci compared to previously and newly identified loci and found slight increases: from 3.0 to 3.3% for males and from 2.7 to 3.0% for females. -
Multi-Ancestry GWAS of the Electrocardiographic PR Interval Identifies 210 Loci Underlying
bioRxiv preprint doi: https://doi.org/10.1101/712398; this version posted July 30, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Multi-ancestry GWAS of the electrocardiographic PR interval identifies 210 loci underlying 2 cardiac conduction 3 4 Ioanna Ntalla1*, Lu-Chen Weng2, 3*, James H. Cartwright1, Amelia Weber Hall2, 3, Gardar 5 Sveinbjornsson4, Nathan R. Tucker2, 3, Seung Hoan Choi3, Mark D. Chaffin3, Carolina Roselli3, 5 , 6 Michael R. Barnes1, 6, Borbala Mifsud1, 7, Helen R. Warren1, 6, Caroline Hayward8, Jonathan 7 Marten8, James J. Cranley1, Maria Pina Concas9, Paolo Gasparini9, 10, Thibaud Boutin8, Ivana 8 Kolcic11, Ozren Polasek11-13, Igor Rudan14, Nathalia M. Araujo15, Maria Fernanda Lima-Costa16, 9 Antonio Luiz P. Ribeiro17, Renan P. Souza15, Eduardo Tarazona-Santos15, Vilmantas Giedraitis18, 10 Erik Ingelsson19-22, Anubha Mahajan23, Andrew P. Morris23-25, Fabiola Del Greco M.26, Luisa 11 Foco26, Martin Gögele26, Andrew A. Hicks26, James P. Cook24, Lars Lind27, Cecilia M. Lindgren28- 12 30, Johan Sundström31, Christopher P. Nelson32, 33, Muhammad B. Riaz32, 33, Nilesh J. Samani32, 33, 13 Gianfranco Sinagra34, Sheila Ulivi9, Mika Kähönen35, 36, Pashupati P. Mishra37, 38, Nina 14 Mononen37, 38, Kjell Nikus39, 40, Mark J. Caulfield1, 6, Anna Dominiczak41, Sandosh 15 Padmanabhan41, 42, May E. Montasser43, 44, Jeff R. O'Connell43, 44, Kathleen Ryan43, 44, Alan R. 16 Shuldiner43, 44, Stefanie Aeschbacher45, David Conen45, 46, Lorenz Risch47-49, Sébastien Thériault46, 17 50, Nina Hutri-Kähönen51, 52, Terho Lehtimäki37, 38, Leo-Pekka Lyytikäinen37-39, Olli T. -
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 -
A Network-Based Analysis of the Cellular and Genetic Etiology of Disease
A network-based analysis of the cellular and genetic etiology of disease Alexander John Cornish Submitted in part-fulfilment of the requirements for the degree of Doctor of Philosophy of Imperial College London and the Diploma of Imperial College London Department of Life Sciences Imperial College London 2016 1 Declaration The contents of this thesis are my own work unless otherwise specified. The copyright of this thesis rests with the author and is made available under a Creative Commons Attribution Non-Commercial No Derivatives licence. Researchers are free to copy, distribute or transmit the thesis on the condition that they attribute it, that they do not use it for commercial purposes and that they do not alter, transform or build upon it. For any reuse or redistribution, researchers must make clear to others the licence terms of this work. Alexander John Cornish 2 Abstract Thousands of disease-associated loci have been identified in genome-wide association studies (GWAS). These loci can span multiple genes and identifying which, if any, of these genes are causal can be challenging. Multiple methods have been developed to identify causal genes, some of which use networks of physical interactions between proteins. The performance of many of these methods may however be limited by their failure to use data specific to the tissues and cell types that manifest each disease. Furthermore, many network-based approaches may be biased towards better-studied genes. In order to use data specific to a disease-manifesting cell type to identify disease- associated genes, it is first necessary to identify the disease-manifesting cell types. -
Genome-Wide Association of Multiple Complex Traits in Outbred Mice by Ultra Low-Coverage Sequencing
Europe PMC Funders Group Author Manuscript Nat Genet. Author manuscript; available in PMC 2017 January 04. Published in final edited form as: Nat Genet. 2016 August ; 48(8): 912–918. doi:10.1038/ng.3595. Europe PMC Funders Author Manuscripts Genome-wide association of multiple complex traits in outbred mice by ultra low-coverage sequencing Jérôme Nicod1, Robert W. Davies1, Na Cai1, Carl Hassett2, Leo Goodstadt1, Cormac Cosgrove3, Benjamin K Yee4, Vikte Lionikaite5, Rebecca E McIntyre6, Carol Ann Remme7, Elisabeth M. Lodder7, Jennifer S. Gregory5, Tertius Hough2, Russell Joynson2, Hayley Phelps2, Barbara Nell2, Clare Rowe2, Joe Wood2, Alison Walling2, Nasrin Bopp1, Amarjit Bhomra1, Polinka Hernandez-Pliego1, Jacques Callebert8, Richard M. Aspden5, Nick P Talbot9, Peter A Robbins9, Mark Harrison2, Martin Fray2, Jean-Marie Launay8, Yigal M. Pinto7, David A. Blizard10, Connie R. Bezzina7, David J Adams6, Paul Franken11, Tom Weaver2, Sara Wells2, Steve DM Brown12, Paul K Potter12, Paul Klenerman3, Arimantas Lionikas5, Richard Mott1,13, and Jonathan Flint1,14 1Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom 2Mary Lyon Centre, MRC Harwell, Harwell Science and Innovation Campus, United Kingdom 3Peter Medawar Building for Pathogen Research, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom 4Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China 5School of Medicine, Medical Sciences and Nutrition, College of Life Sciences and Medicine, University of Aberdeen, Aberdeen, -
Connecting Differentially Expressed Genes, Mirnas, and Lncrnas
School of Sciences and Engineering Regulatory Networks in Non-Small Cell Lung Cancer: Connecting Differentially Expressed Genes, miRNAs, and lncRNAs A Thesis Submitted to the: The Biotechnology Graduate Program In partial fulfillment of the requirements for The degree of Master of Science in Biotechnology By: Jasmine Kamal Omran Bachelor of Science in Human Biology, University of California San Diego Under the supervision of Dr. Hassan Azzazy Professor, Department of Chemistry, The American University in Cairo December/2016 The American University in Cairo School of Science and Engineering Regulatory Networks in Non- Small Cell Lung Cancer: Connecting Differentially Expressed Genes, miRNAs, and lncRNAs A Thesis Submitted by: Jasmine Kamal Omran To the Biotechnology Graduate Program December 2016 In partial fulfillment of the requirements for the degree of Master of Science in Biotechnology Has been approved by: Thesis Committee Supervisor/Chair ________________________________________________ Affiliation_____________________________________________________________________ Thesis Committee Supervisor _____________________________________________________ Affiliation_____________________________________________________________________ Thesis Committee Reader/Examiner ________________________________________________ Affiliation_____________________________________________________________________ Thesis Committee Reader/Examiner ________________________________________________ Affiliation_____________________________________________________________________ -
Identification of Host Factors Associated with the Development Of
viruses Article Identification of Host Factors Associated with the Development of Equine Herpesvirus Myeloencephalopathy by Transcriptomic Analysis of Peripheral Blood Mononuclear Cells from Horses Lila M. Zarski 1, Kim S. Giessler 1, Sarah I. Jacob 1 , Patty Sue D. Weber 2, Allison G. McCauley 1, Yao Lee 1 and Gisela Soboll Hussey 1,* 1 Department of Pathobiology and Diagnostic Investigation, Michigan State University, East Lansing, MI 48824, USA; [email protected] (L.M.Z.); [email protected] (K.S.G.); [email protected] (S.I.J.); [email protected] (A.G.M.); [email protected] (Y.L.) 2 Department of Large Animal Clinical Sciences, Michigan State University, East Lansing, MI 48824, USA; [email protected] * Correspondence: [email protected] Abstract: Equine herpesvirus-1 is the cause of respiratory disease, abortion, and equine herpesvirus myeloencephalopathy (EHM) in horses worldwide. EHM affects as many as 14% of infected horses and a cell-associated viremia is thought to be central for EHM pathogenesis. While EHM is infrequent Citation: Zarski, L.M.; Giessler, K.S.; in younger horses, up to 70% of aged horses develop EHM. The aging immune system likely con- Jacob, S.I.; Weber, P.S.D.; McCauley, tributes to EHM pathogenesis; however, little is known about the host factors associated with clinical A.G.; Lee, Y.; Soboll Hussey, G. EHM. Here, we used the “old mare model” to induce EHM following EHV-1 infection. Peripheral Identification of Host Factors blood mononuclear cells (PBMCs) of horses prior to infection and during viremia were collected Associated with the Development of and RNA sequencing with differential gene expression was used to compare the transcriptome of Equine Herpesvirus horses that did (EHM group) and did not (non-EHM group) develop clinical EHM. -
Towards Retinal Repair: Analysis of Photoreceptor Precursor Cells and Their Cell Surface Molecules
Towards retinal repair: analysis of photoreceptor precursor cells and their cell surface molecules Ya-Ting Han University College London Institute of Child Health A thesis submitted for the degree of Philosophiae Doctor For the incredible cells that drive me here. ii Acknowledgements I would like to firstly thank my supervisor Prof. Jane Sowden for her consistent support, encouragement and advice throughout my PhD. I still remember when I just started my PhD and wanted some dendritic cells in a control experiment for some even not so exciting markers, Jane instantly contacted her colleagues to provide me these cells. Cases as such are countless. I have been encouraged to develop my own research ideas and Jane has always been supporting. It is through all these that I confidently and happily conducted my studies here. I am very happy that I chose the right supervisor. Thank you, Jane! I would also like to thank my secondary supervisor Prof. Robin Ali for his encouragements throughout, Dr. Janny Morgan for her advice during my PhD upgrade, Prof. Andy Copp, Prof. David Muller, Dr. Kenth Gustafsson, Dr. Andy Stoker, Dr. Juan-Pedro Martinez-Barbera, and Dr. Patrizia Ferretti for helpful discussion and advices. Thanks to Dr. Kevin Mills and Dr. Wendy Heywood for their supports with mass spectrometry, especially Wendy for her unlimited kind and generous help during all my time with mass spectrometry. Thanks to Dan who helped and advised me in molecular cloning. Thanks to Rachael who performed all the injections for cell transplantation. Thanks to Jorn who showed me the techniques when I just entered the lab and helped me with my first cell transplantation.