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(19) TZZ¥ ZZ_T (11) EP 3 260 540 A1 (12) EUROPEAN PATENT APPLICATION (43) Date of publication: (51) Int Cl.: 27.12.2017 Bulletin 2017/52 C12N 15/113 (2010.01) A61K 9/127 (2006.01) A61K 31/713 (2006.01) C12Q 1/68 (2006.01) (21) Application number: 17000579.7 (22) Date of filing: 12.11.2011 (84) Designated Contracting States: • Sarma, Kavitha AL AT BE BG CH CY CZ DE DK EE ES FI FR GB Philadelphia, PA 19146 (US) GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO • Borowsky, Mark PL PT RO RS SE SI SK SM TR Needham, MA 02494 (US) • Ohsumi, Toshiro Kendrick (30) Priority: 12.11.2010 US 412862 P Cambridge, MA 02141 (US) 20.12.2010 US 201061425174 P 28.07.2011 US 201161512754 P (74) Representative: Clegg, Richard Ian et al Mewburn Ellis LLP (62) Document number(s) of the earlier application(s) in City Tower accordance with Art. 76 EPC: 40 Basinghall Street 11840099.3 / 2 638 163 London EC2V 5DE (GB) (71) Applicant: The General Hospital Corporation Remarks: Boston, MA 02114 (US) •Thecomplete document including Reference Tables and the Sequence Listing can be downloaded from (72) Inventors: the EPO website • Lee, Jeannie T •This application was filed on 05-04-2017 as a Boston, MA 02114 (US) divisional application to the application mentioned • Zhao, Jing under INID code 62. San Diego, CA 92122 (US) •Claims filed after the date of receipt of the divisional application (Rule 68(4) EPC). (54) POLYCOMB-ASSOCIATED NON-CODING RNAS (57) This invention relates to long non-coding RNAs (IncRNAs), libraries of those ncRNAs that bind chromatin modifiers, such as Polycomb Repressive Complex 2, inhibitory nucleic acids and methods and compositions for targeting IncRNAs. -
Prevalence and Significance of Nonsense-‐Mediated Mrna Decay
Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms By Courtney Elizabeth French A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Molecular and Cell Biology in the Graduate Division of the University of California, Berkeley Committee in charge: Professor Steven E. Brenner, Co-Chair Professor Donald C. Rio, Co-Chair Professor Britt A. Glaunsinger Professor Sandrine Dudoit Spring 2016 Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms Copyright 2016 by Courtney Elizabeth French Abstract Prevalence and Significance of Nonsense-Mediated mRNA Decay Coupled with Alternative Splicing in Diverse Eukaryotic Organisms by Courtney Elizabeth French Doctor of Philosophy in Molecular and Cell Biology University of California, Berkeley Professor Steven E. Brenner, Co-Chair Professor Donald C. Rio, Co-Chair Alternative splicing plays a crucial role in increasing the amount of protein diversity and in regulating gene expression at the post-transcriptional level. In humans, almost all genes produce more than one mRNA isoform and, while the fraction varies, many other species also have a substantial number of alternatively spliced genes. Alternative splicing is regulated by splicing factors, often in a developmental time- or tissue-specific manner. Mis- regulation of alternative splicing, via mutations in splice sites, splicing regulatory elements, or splicing factors, can lead to disease states, including cancers. Thus, characterizing how alternative splicing shapes the transcriptome will lead to greater insights into the regulation of numerous cellular pathways and many aspects of human health. A critical tool for investigating alternative splicing is high-throughput mRNA sequencing (RNA-seq). -
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, -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Imputation of Exome Sequence Variants Into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project
ARTICLE Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project Paul L. Auer,1,17 Jill M. Johnsen,2,3,17 Andrew D. Johnson,4,17 Benjamin A. Logsdon,1,17 Leslie A. Lange,5,17 Michael A. Nalls,6 Guosheng Zhang,5 Nora Franceschini,5 Keolu Fox,3 Ethan M. Lange,5 Stephen S. Rich,7 Christopher J. O’Donnell,4 Rebecca D. Jackson,8 Robert B. Wallace,9 Zhao Chen,10 Timothy A. Graubert,11 James G. Wilson,12 Hua Tang,13,17 Guillaume Lettre,14,17 Alex P. Reiner,1,6,17,* Santhi K. Ganesh,15,17 and Yun Li5,16,17,* Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly pene- trant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants asso- ciated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demon- strating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino À acid substitution of the thrombpoietin receptor gene (p ¼ 1.5 3 10 11). -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase -
Mygene.Info R Client
MyGene.info R Client Adam Mark, Ryan Thompson, Chunlei Wu May 19, 2021 Contents 1 Overview ..............................2 2 Gene Annotation Service ...................2 2.1 getGene .............................2 2.2 getGenes ............................2 3 Gene Query Service ......................3 3.1 query ..............................3 3.2 queryMany ...........................4 4 makeTxDbFromMyGene....................5 5 Tutorial, ID mapping .......................6 5.1 Mapping gene symbols to Entrez gene ids ........6 5.2 Mapping gene symbols to Ensembl gene ids .......7 5.3 When an input has no matching gene ...........8 5.4 When input ids are not just symbols ............8 5.5 When an input id has multiple matching genes ......9 5.6 Can I convert a very large list of ids?............ 11 6 References ............................. 11 MyGene.info R Client 1 Overview MyGene.Info provides simple-to-use REST web services to query/retrieve gene annotation data. It’s designed with simplicity and performance emphasized. mygene is an easy-to-use R wrapper to access MyGene.Info services. 2 Gene Annotation Service 2.1 getGene • Use getGene, the wrapper for GET query of "/gene/<geneid>" service, to return the gene object for the given geneid. > gene <- getGene("1017", fields="all") > length(gene) [1] 1 > gene["name"] [[1]] NULL > gene["taxid"] [[1]] NULL > gene["uniprot"] [[1]] NULL > gene["refseq"] [[1]] NULL 2.2 getGenes • Use getGenes, the wrapper for POST query of "/gene" service, to return the list of gene objects for the given character vector of geneids. > getGenes(c("1017","1018","ENSG00000148795")) DataFrame with 3 rows and 7 columns 2 MyGene.info R Client query _id X_version entrezgene name <character> <character> <integer> <character> <character> 1 1017 1017 4 1017 cyclin dependent kin. -
Arginine-Enriched Mixed-Charge Domains Provide Cohesion for Nuclear Speckle Condensation
bioRxiv preprint doi: https://doi.org/10.1101/771592; this version posted September 16, 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. 1 Arginine-enriched mixed-charge domains provide cohesion for nuclear 2 speckle condensation 3 4 Jamie A. Greig1, Tu Anh Nguyen1, Michelle Lee1, Alex S. Holehouse2, Ammon E. 5 Posey2, Rohit V. Pappu2, and Gregory JeDD1* 6 7 1Temasek Life Sciences Laboratory & Department of Biological Sciences, The 8 National University of Singapore, Singapore 117604 9 2Department of BiomeDical Engineering anD Center for Science & Engineering of 10 Living Systems (CSELS), Washington University in St. Louis, St. Louis, MO 63130, 11 USA 12 13 *CorresponDence: [email protected] 14 15 Abstract 16 Low-complexity protein Domains promote the formation of various biomolecular 17 conDensates. However, in many cases, the precise sequence features governing 18 conDensate formation anD iDentity remain unclear. Here, we investigate the role of 19 intrinsically DisordereD mixeD-charge Domains (MCDs) in nuclear speckle 20 conDensation. Proteins composeD exclusively of arginine/aspartic-aciD DipeptiDe 21 repeats unDergo length-DepenDent conDensation anD speckle incorporation. 22 Substituting arginine with lysine in synthetic anD natural speckle-associateD MCDs 23 abolishes these activities, iDentifying a key role for multivalent contacts through 24 arginine’s guaniDinium ion. MCDs can synergise with a speckle-associateD RNA 25 recognition motif to promote speckle specificity anD resiDence. MCD behaviour is 26 tuneable through net-charge: increasing negative charge abolishes conDensation anD 27 speckle incorporation. -
Bioinformatic Analysis of Next‑Generation Sequencing Data to Identify Dysregulated Genes in Fibroblasts of Idiopathic Pulmonary Fibrosis
INTERNATIONAL JOURNAL OF MOleCular meDICine 43: 1643-1656, 2019 Bioinformatic analysis of next‑generation sequencing data to identify dysregulated genes in fibroblasts of idiopathic pulmonary fibrosis CHAU‑CHYUN SHEU1-3, WEI‑AN CHANG1,2, MING‑JU TSAI1-3, SSU‑HUI LIAO1, INN‑WEN CHONG2,3 and PO-LIN KUO1 1Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University; 2Division of Pulmonary and Critical Care Medicine, Kaohsiung Medical University Hospital; 3Department of Internal Medicine, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 807, Taiwan, R.O.C. Received October 7, 2018; Accepted January 29, 2019 DOI: 10.3892/ijmm.2019.4086 Abstract. Idiopathic pulmonary fibrosis (IPF) is a lethal and miRNA expression data, combined with GEO verifica- fibrotic lung disease with an increasing global burden. It is tion, finally identified Homo sapiens (hsa)-miR-1254-INKA2 hypothesized that fibroblasts have a number of functions that and hsa-miR-766-3p-INKA2 as the potential miRNA-mRNA may affect the development and progression of IPF. However, interactions in IPF fibroblasts. In summary, the results the present understanding of cellular and molecular mecha- of the present study suggest that dysregulation of PAX8, nisms associated with fibroblasts in IPF remains limited. hsa-miR-1254-INKA2 and hsa-miR-766-3p-INKA2 may The present study aimed to identify the dysregulated genes promote the proliferation and survival of IPF fibroblasts. In in IPF fibroblasts, elucidate their functions and explore the functional analysis of the dysregulated genes, a marked potential microRNA (miRNA)‑mRNA interactions. mRNA association between fibroblasts and the ECM was identified. -
CRISPR/Cas9 Interrogation of the Mouse Pcdhg Gene Cluster 4 Reveals a Crucial Isoform-Specific Role for Pcdhgc4
bioRxiv preprint doi: https://doi.org/10.1101/739508; this version posted August 19, 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 4.0 International license. 1 2 3 CRISPR/Cas9 interrogation of the mouse Pcdhg gene cluster 4 reveals a crucial isoform-specific role for Pcdhgc4 5 6 Andrew M. Garrett1, 3,*, Peter J. Bosch2, David M. Steffen2, Leah C. Fuller2, Charles G. Marcucci2, Alexis A. 7 Koch1, Preeti Bais3, Joshua A. Weiner2,*, and Robert W. Burgess3,* 8 9 1 Wayne State University, Department of Pharmacology, Department of Ophthalmology, Visual, and 10 Anatomical Sciences, Detroit, MI. 11 2 University of Iowa, Department of Biology and Iowa Neuroscience Institute, Iowa City, IA 12 3 The Jackson Laboratory, Bar Harbor, ME 13 * Co-corresponding authors 1 bioRxiv preprint doi: https://doi.org/10.1101/739508; this version posted August 19, 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 4.0 International license. 14 ABSTRACT 15 The mammalian Pcdhg gene cluster encodes a family of 22 cell adhesion molecules, the gamma- 16 Protocadherins (γ-Pcdhs), critical for neuronal survival and neural circuit formation. The extent to which 17 isoform diversity–a γ-Pcdh hallmark–is required for their functions remains unclear. We used a 18 CRISPR/Cas9 approach to reduce isoform diversity, targeting each Pcdhg variable exon with pooled 19 sgRNAs to generate an allelic series of 26 mouse lines with 1 to 21 isoforms disrupted via discrete indels 20 at guide sites and/or larger deletions/rearrangements. -
Identification of Tgfβ-Related Genes Regulated in Murine Osteoarthritis and Chondrocyte Hypertrophy by Comparison of Multiple Microarray Datasets
http://hdl.handle.net/1765/109466 Identification of TGFβ-related genes regulated in murine osteoarthritis and chondrocyte hypertrophy by comparison of multiple microarray datasets Laurie M.G. de Kroon1,2,&, Guus G.H. van den Akker1,&, Bent Brachvogel3,4, Roberto Narcisi2, Daniele Belluoccio5, Florien Jenner6, John F. Bateman5, Christopher B. Little7, Pieter Brama8, Esmeralda N. Blaney Davidson1, Peter M. van der Kraan1, Gerjo J.V.M. van Osch2,9* 1Department of Rheumatology, Experimental Rheumatology, Radboud University Medical Center, Nijmegen, the Netherlands 2Department of Orthopedics, Erasmus MC University Medical Center, Rotterdam, the Netherlands 3Center for Biochemistry, Medical Faculty, University of Cologne, Cologne, Germany 4Department of Pediatrics and Adolescent Medicine, Experimental Neonatology, Medical Faculty, University of Cologne, Cologne, Germany 5Murdoch Childrens Research Institute, Royal Children’s Hospital, Parkville, Victoria, Australia 6Equine University Hospital, University of Veterinary Medicine, Vienna, Austria 7Raymond Purves Bone and Joint Research Laboratories, Kolling Institute of Medical Research, University of Sydney, St Leonards, New South Wales, Australia 8Veterinary Clinical Sciences, School of Veterinary Medicine, University College Dublin, Dublin, Ireland 9Department of Otorhinolaryngology, Erasmus MC University Medical Center, Rotterdam, the Netherlands &Both authors contributed equally *Corresponding author: Gerjo van Osch ([email protected]) Address for correspondence: Erasmus MC, Departments -
Functional Analysis of Structural Variation in the 2D and 3D Human Genome
FUNCTIONAL ANALYSIS OF STRUCTURAL VARIATION IN THE 2D AND 3D HUMAN GENOME by Conor Mitchell Liam Nodzak A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Bioinformatics and Computational Biology Charlotte 2019 Approved by: Dr. Xinghua Mindy Shi Dr. Rebekah Rogers Dr. Jun-tao Guo Dr. Adam Reitzel ii c 2019 Conor Mitchell Liam Nodzak ALL RIGHTS RESERVED iii ABSTRACT CONOR MITCHELL LIAM NODZAK. Functional analysis of structural variation in the 2D and 3D human genome. (Under the direction of DR. XINGHUA MINDY SHI) The human genome consists of over 3 billion nucleotides that have an average distance of 3.4 Angstroms between each base, which equates to over two meters of DNA contained within the 125 µm3 volume diploid cell nuclei. The dense compaction of chromatin by the supercoiling of DNA forms distinct architectural modules called topologically associated domains (TADs), which keep protein-coding genes, noncoding RNAs and epigenetic regulatory elements in close nuclear space. It has recently been shown that these conserved chromatin structures may contribute to tissue-specific gene expression through the encapsulation of genes and cis-regulatory elements, and mutations that affect TADs can lead to developmental disorders and some forms of cancer. At the population-level, genomic structural variation contributes more to cumulative genetic difference than any other class of mutation, yet much remains to be studied as to how structural variation affects TADs. Here, we study the func- tional effects of structural variants (SVs) through the analysis of chromatin topology and gene activity for three trio families sampled from genetically diverse popula- tions from the Human Genome Structural Variation Consortium.