Comparison of Selection Signatures Between Korean Native and Commercial Chickens Using 600K SNP Array Data
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Myosin Myth4-FERM Structures Highlight Important Principles of Convergent Evolution
Myosin MyTH4-FERM structures highlight important principles of convergent evolution Vicente José Planelles-Herreroa,b, Florian Blanca,c, Serena Sirigua, Helena Sirkiaa, Jeffrey Clausea, Yannick Souriguesa, Daniel O. Johnsrudd, Beatrice Amiguesa, Marco Cecchinic, Susan P. Gilberte, Anne Houdussea,1,2, and Margaret A. Titusd,1,2 aStructural Motility, Institut Curie, CNRS, UMR 144, PSL Research University, F-75005 Paris, France; bUPMC Université de Paris 6, Institut de Formation Doctorale, Sorbonne Universités, 75252 Paris Cedex 05, France; cLaboratoire d’Ingénierie des Fonctions Moléculaires, Institut de Science et d’Ingénierie Supramoléculaires, UMR 7006 CNRS, Université de Strasbourg, F-67083 Strasbourg Cedex, France; dDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN 55455; and eDepartment of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY 12180 Edited by James A. Spudich, Stanford University School of Medicine, Stanford, CA, and approved March 31, 2016 (received for review January 15, 2016) Myosins containing MyTH4-FERM (myosin tail homology 4-band (Fig. 1). These MF myosins are widespread and likely quite an- 4.1, ezrin, radixin, moesin, or MF) domains in their tails are found cient because they are found in many different branches of the in a wide range of phylogenetically divergent organisms, such as phylogenetic tree (5, 6), including Opisthokonts (which includes humans and the social amoeba Dictyostelium (Dd). Interestingly, Metazoa, unicellular Holozoa, and Fungi), Amoebozoa, and the evolutionarily distant MF myosins have similar roles in the exten- SAR (Stramenopiles, Alveolates, and Rhizaria) (Fig. 1 A and B). sion of actin-filled membrane protrusions such as filopodia and Over the course of hundreds of millions years of parallel evolution bind to microtubules (MT), suggesting that the core functions of the MF myosins have acquired or maintained roles in the formation these MF myosins have been highly conserved over evolution. -
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. -
Spectrum of MYO7A Mutations in an Indigenous South African
G C A T T A C G G C A T genes Article Spectrum of MYO7A Mutations in an Indigenous South African Population Further Elucidates the Nonsyndromic Autosomal Recessive Phenotype of DFNB2 to Include Both Homozygous and Compound Heterozygous Mutations Rosemary Ida Kabahuma 1,2,*, Wolf-Dieter Schubert 2, Christiaan Labuschagne 3, Denise Yan 4, Susan Halloran Blanton 4,5 , Michael Sean Pepper 6 and Xue Zhong Liu 4,5,* 1 Department of Otorhinolaryngology, University of Pretoria, Pretoria 0001, South Africa 2 Departments of Biochemistry, Genetics and Microbiology, Faculty of Natural and Agricultural Sciences, University of Pretoria, Pretoria 0001, South Africa; [email protected] 3 Inqaba Biotechnical Industries, Pretoria 0002, South Africa; [email protected] 4 Department Otolaryngology, University of Miami Miller School of Medicine, Miami, FL 33136, USA; [email protected] (D.Y.); [email protected] (S.H.B.) 5 Dr. John T. Macdonald Foundation Department of Human Genetics, and John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136, USA 6 Department Immunology and SAMRC Extramural Unit for Stem Cell Research and Therapy, Faculty of Health Sciences, Institute for Cellular and Molecular Medicine, University of Pretoria, Citation: Kabahuma, R.I.; Pretoria 0001, South Africa; [email protected] Schubert, W.-D.; Labuschagne, C.; * Correspondence: [email protected] (R.I.K.); [email protected] (X.Z.L.) Yan, D.; Blanton, S.H.; Pepper, M.S.; Liu, X.Z. Spectrum of MYO7A Abstract: MYO7A gene encodes unconventional myosin VIIA, which, when mutated, causes a phe- Mutations in an Indigenous South notypic spectrum ranging from recessive hearing loss DFNB2 to deaf-blindness, Usher Type 1B African Population Further (USH1B). -
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 -
MYO7A Gene Myosin VIIA
MYO7A gene myosin VIIA Normal Function The MYO7A gene provides instructions for making a protein called myosin VIIA, which is part of a group of proteins called unconventional myosins. These proteins, which have similar structures, help transport molecules within cells. Myosins interact with actin, a protein that is important for cell movement and shape. Researchers believe that myosins use long filaments of actin as tracks along which to transport other molecules. Myosin VIIA is made in the inner ear and in the retina, which is the light-sensitive tissue at the back of the eye. In the inner ear, myosin VIIA plays a role in the development and maintenance of hairlike projections called stereocilia. Stereocilia, which are rich in actin, line the inner ear and bend in response to sound waves. This bending motion is critical for converting sound waves to nerve impulses, which are then transmitted to the brain. Stereocilia are also elements of the vestibular system, the part of the inner ear that helps maintain the body's balance and orientation in space. Bending of these stereocilia is needed to transmit signals from the vestibular system to the brain. In the retina, myosin VIIA is found primarily in a thin layer of cells called the retinal pigment epithelium (RPE). Myosin VIIA probably plays a role in the development and maintenance of this tissue, which supports and nourishes the retina. Research suggests that one function of myosin VIIA is to carry small sacs of pigment (called melanosomes) within the RPE. This pigment is necessary for normal vision. Myosin VIIA is also found in other parts of the retina, where it likely carries additional proteins and molecules that are important for vision. -
CSE642 Final Version
Eindhoven University of Technology MASTER Dimensionality reduction of gene expression data Arts, S. Award date: 2018 Link to publication Disclaimer This document contains a student thesis (bachelor's or master's), as authored by a student at Eindhoven University of Technology. Student theses are made available in the TU/e repository upon obtaining the required degree. The grade received is not published on the document as presented in the repository. The required complexity or quality of research of student theses may vary by program, and the required minimum study period may vary in duration. General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain Eindhoven University of Technology MASTER THESIS Dimensionality Reduction of Gene Expression Data Author: S. (Sako) Arts Daily Supervisor: dr. V. (Vlado) Menkovski Graduation Committee: dr. V. (Vlado) Menkovski dr. D.C. (Decebal) Mocanu dr. N. (Nikolay) Yakovets May 16, 2018 v1.0 Abstract The focus of this thesis is dimensionality reduction of gene expression data. I propose and test a framework that deploys linear prediction algorithms resulting in a reduced set of selected genes relevant to a specified case. Abstract In cancer research there is a large need to automate parts of the process of diagnosis, this is mainly to reduce cost, make it faster and more accurate. -
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 -
Clinical Validation of the Tempus Xt Next-Generation Targeted Oncology Sequencing Assay
www.oncotarget.com Oncotarget, 2019, Vol. 10, (No. 24), pp: 2384-2396 Research Paper Clinical validation of the tempus xT next-generation targeted oncology sequencing assay Nike Beaubier1, Robert Tell1, Denise Lau1, Jerod R. Parsons1, Stephen Bush1, Jason Perera1, Shelly Sorrells1, Timothy Baker1, Alan Chang1, Jackson Michuda1, Catherine Iguartua1, Shelley MacNeil1, Kaanan Shah1, Philip Ellis1, Kimberly Yeatts1, Brett Mahon1, Timothy Taxter1, Martin Bontrager1, Aly Khan1, Robert Huether1, Eric Lefkofsky1 and Kevin P. White1 1Tempus Labs Inc., Chicago, IL 60654, USA Correspondence to: Nike Beaubier, email: [email protected] Kevin P. White, email: [email protected] Keywords: tumor profiling, next-generation sequencing assay validation Received: August 03, 2018 Accepted: February 03, 2019 Published: March 22, 2019 Copyright: Beaubier et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. ABSTRACT We developed and clinically validated a hybrid capture next generation sequencing assay to detect somatic alterations and microsatellite instability in solid tumors and hematologic malignancies. This targeted oncology assay utilizes tumor- normal matched samples for highly accurate somatic alteration calling and whole transcriptome RNA sequencing for unbiased identification of gene fusion events. The assay was validated with a combination of clinical specimens and cell lines, and recorded a sensitivity of 99.1% for single nucleotide variants, 98.1% for indels, 99.9% for gene rearrangements, 98.4% for copy number variations, and 99.9% for microsatellite instability detection. This assay presents a wide array of data for clinical management and clinical trial enrollment while conserving limited tissue. -
Mitoxplorer, a Visual Data Mining Platform To
mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, Cecilia Garcia-Perez, José Villaveces, Salma Gamal, Giovanni Cardone, Fabiana Perocchi, et al. To cite this version: Annie Yim, Prasanna Koti, Adrien Bonnard, Fabio Marchiano, Milena Dürrbaum, et al.. mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dy- namics and mutations. Nucleic Acids Research, Oxford University Press, 2020, 10.1093/nar/gkz1128. hal-02394433 HAL Id: hal-02394433 https://hal-amu.archives-ouvertes.fr/hal-02394433 Submitted on 4 Dec 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License Nucleic Acids Research, 2019 1 doi: 10.1093/nar/gkz1128 Downloaded from https://academic.oup.com/nar/advance-article-abstract/doi/10.1093/nar/gkz1128/5651332 by Bibliothèque de l'université la Méditerranée user on 04 December 2019 mitoXplorer, a visual data mining platform to systematically analyze and visualize mitochondrial expression dynamics and mutations Annie Yim1,†, Prasanna Koti1,†, Adrien Bonnard2, Fabio Marchiano3, Milena Durrbaum¨ 1, Cecilia Garcia-Perez4, Jose Villaveces1, Salma Gamal1, Giovanni Cardone1, Fabiana Perocchi4, Zuzana Storchova1,5 and Bianca H. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
Literature Mining Sustains and Enhances Knowledge Discovery from Omic Studies
LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES by Rick Matthew Jordan B.S. Biology, University of Pittsburgh, 1996 M.S. Molecular Biology/Biotechnology, East Carolina University, 2001 M.S. Biomedical Informatics, University of Pittsburgh, 2005 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Rick Matthew Jordan It was defended on December 2, 2015 and approved by Shyam Visweswaran, M.D., Ph.D., Associate Professor Rebecca Jacobson, M.D., M.S., Professor Songjian Lu, Ph.D., Assistant Professor Dissertation Advisor: Vanathi Gopalakrishnan, Ph.D., Associate Professor ii Copyright © by Rick Matthew Jordan 2016 iii LITERATURE MINING SUSTAINS AND ENHANCES KNOWLEDGE DISCOVERY FROM OMIC STUDIES Rick Matthew Jordan, M.S. University of Pittsburgh, 2016 Genomic, proteomic and other experimentally generated data from studies of biological systems aiming to discover disease biomarkers are currently analyzed without sufficient supporting evidence from the literature due to complexities associated with automated processing. Extracting prior knowledge about markers associated with biological sample types and disease states from the literature is tedious, and little research has been performed to understand how to use this knowledge to inform the generation of classification models from ‘omic’ data. Using pathway analysis methods to better understand the underlying biology of complex diseases such as breast and lung cancers is state-of-the-art. However, the problem of how to combine literature- mining evidence with pathway analysis evidence is an open problem in biomedical informatics research. -
Wo 2010/081001 A2
(12) INTERNATIONAL APPLICATION PUBLISHED UNDER THE PATENT COOPERATION TREATY (PCT) (19) World Intellectual Property Organization International Bureau (10) International Publication Number (43) International Publication Date 15 July 2010 (15.07.2010) WO 2010/081001 A2 (51) International Patent Classification: (81) Designated States (unless otherwise indicated, for every C12Q 1/68 (2006.01) kind of national protection available): AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BR, BW, BY, BZ, (21) International Application Number: CA, CH, CL, CN, CO, CR, CU, CZ, DE, DK, DM, DO, PCT/US20 10/020501 DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, (22) International Filing Date: HN, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KN, KP, ! January 2010 (08.01 .2010) KR, KZ, LA, LC, LK, LR, LS, LT, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, (25) Filing Language: English NO, NZ, OM, PE, PG, PH, PL, PT, RO, RS, RU, SC, SD, (26) Publication Language: English SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW. (30) Priority Data: 61/143,598 9 January 2009 (09.01 .2009) US (84) Designated States (unless otherwise indicated, for every 61/187,776 17 June 2009 (17.06.2009) US kind of regional protection available): ARIPO (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, (71) Applicant (for all designated States except US): THE ZW), Eurasian (AM, AZ, BY, KG, KZ, MD, RU, TJ, REGENTS OF THE UNIVERSITY OF MICHIGAN TM), European (AT, BE, BG, CH, CY, CZ, DE, DK, EE, [US/US]; 1214 South University, 2nd Floor, Ann Arbor, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, Michigan 48104 (US).