Chapter 8 Exome Sequencing in Patient- Parent Trios Reveals New Candidate Genes for Early-Onset Primary Sclerosing Cholangitis
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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. -
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 -
Fine-Mapping of 150 Breast Cancer Risk Regions Identifies 178 High Confidence Target Genes
bioRxiv preprint doi: https://doi.org/10.1101/521054; this version posted January 15, 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. Fine-mapping of 150 breast cancer risk regions identifies 178 high confidence target genes Laura Fachal1, Hugues Aschard2-4,275, Jonathan Beesley5,275, Daniel R. Barnes6, Jamie Allen6, Siddhartha Kar1, Karen A. Pooley6, Joe Dennis6, Kyriaki Michailidou6, 7, Constance Turman4, Penny Soucy8, Audrey Lemaçon8, Michael Lush6, Jonathan P. Tyrer1, Maya Ghoussaini1, Mahdi Moradi Marjaneh5, Xia Jiang3, Simona Agata9, Kristiina Aittomäki10, M. Rosario Alonso11, Irene L. Andrulis12, 13, Hoda Anton-Culver14, Natalia N. Antonenkova15, Adalgeir Arason16, 17, Volker Arndt18, Kristan J. Aronson19, Banu K. Arun20, Bernd Auber21, Paul L. Auer22, 23, Jacopo Azzollini24, Judith Balmaña25, Rosa B. Barkardottir16, 17, Daniel Barrowdale6, Alicia Beeghly-Fadiel26, Javier Benitez27, 28, Marina Bermisheva29, Katarzyna Białkowska30, Amie M. Blanco31, Carl Blomqvist32, 33, William Blot26, 34, Natalia V. Bogdanova15, 35, 36, Stig E. Bojesen37- 39, Manjeet K. Bolla6, Bernardo Bonanni40, Ake Borg41, Kristin Bosse42, Hiltrud Brauch43-45, Hermann Brenner18, 45, 46, Ignacio Briceno47, 48, Ian W. Brock49, Angela Brooks-Wilson50, 51, Thomas Brüning52, Barbara Burwinkel53, 54, Saundra S. Buys55, Qiuyin Cai26, Trinidad Caldés56, Maria A. Caligo57, Nicola J. Camp58, Ian Campbell59, 60, Federico Canzian61, Jason S. Carroll62, Brian D. Carter63, Jose E. Castelao64, Jocelyne Chiquette65, Hans Christiansen35, Wendy K. Chung66, Kathleen B.M. Claes67, Christine L. Clarke68, GEMO Study Collaborators69-71, EMBRACE Collaborators6, J. -
Evolution of Vertebrate Solute Carrier Family 9B
etics & E en vo g lu t lo i y o h n a P r f y Journal of Phylogenetics & Holmes et al., J Phylogen Evolution Biol 2016, 4:3 o B l i a o n l r o DOI: 10.4172/2329-9002.1000167 u g o y J Evolutionary Biology ISSN: 2329-9002 Research Article Open Access Evolution of Vertebrate Solute Carrier Family 9B Genes and Proteins (SLC9B): Evidence for a Marsupial Origin for Testis Specific SLC9B1 from an Ancestral Vertebrate SLC9B2 Gene Roger S Holmes1*,2, Kimberly D Spradling-Reeves2 and Laura A Cox2 1Eskitis Institute for Drug Discovery and School of Natural Sciences, Griffith University, Nathan, QLD, Australia 2Department of Genetics and Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, Texas, USA Abstract SLC9B genes and proteins are members of the sodium/lithium hydrogen antiporter family which function as solute exchangers within cellular membranes of mammalian tissues. SLC9B2 and SLC9B1 amino acid sequences and structures and SLC9B-like gene locations were examined using bioinformatic data from several vertebrate genome projects. Vertebrate SLC9B2 sequences shared 56-98% identity as compared with ~50% identities with mammalian SLC9B1 sequences. Sequence alignments, key amino acid residues and conserved predicted transmembrane structures were also studied. Mammalian SLC9B2 and SLC9B1 genes usually contained 11 or 12 coding exons with differential tissue expression patterns: SLC9B2, broad tissue distribution; and SLC9B1, being testis specific. Transcription factor binding sites and CpG islands within the human SLC9B2 and SLC9B1 gene promoters were identified. Phylogenetic analyses suggested thatSLC9B1 originated in an ancestral marsupial genome from a SLC9B2 gene duplication event. -
Ciliary Dyneins and Dynein Related Ciliopathies
cells Review Ciliary Dyneins and Dynein Related Ciliopathies Dinu Antony 1,2,3, Han G. Brunner 2,3 and Miriam Schmidts 1,2,3,* 1 Center for Pediatrics and Adolescent Medicine, University Hospital Freiburg, Freiburg University Faculty of Medicine, Mathildenstrasse 1, 79106 Freiburg, Germany; [email protected] 2 Genome Research Division, Human Genetics Department, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands; [email protected] 3 Radboud Institute for Molecular Life Sciences (RIMLS), Geert Grooteplein Zuid 10, 6525 KL Nijmegen, The Netherlands * Correspondence: [email protected]; Tel.: +49-761-44391; Fax: +49-761-44710 Abstract: Although ubiquitously present, the relevance of cilia for vertebrate development and health has long been underrated. However, the aberration or dysfunction of ciliary structures or components results in a large heterogeneous group of disorders in mammals, termed ciliopathies. The majority of human ciliopathy cases are caused by malfunction of the ciliary dynein motor activity, powering retrograde intraflagellar transport (enabled by the cytoplasmic dynein-2 complex) or axonemal movement (axonemal dynein complexes). Despite a partially shared evolutionary developmental path and shared ciliary localization, the cytoplasmic dynein-2 and axonemal dynein functions are markedly different: while cytoplasmic dynein-2 complex dysfunction results in an ultra-rare syndromal skeleto-renal phenotype with a high lethality, axonemal dynein dysfunction is associated with a motile cilia dysfunction disorder, primary ciliary dyskinesia (PCD) or Kartagener syndrome, causing recurrent airway infection, degenerative lung disease, laterality defects, and infertility. In this review, we provide an overview of ciliary dynein complex compositions, their functions, clinical disease hallmarks of ciliary dynein disorders, presumed underlying pathomechanisms, and novel Citation: Antony, D.; Brunner, H.G.; developments in the field. -
Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations
IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, VOL. X, NO. X, MONTHXXX 20XX 1 Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations Davide Chicco, Fernando Palluzzi, and Marco Masseroli Abstract—Biomolecular controlled annotations have become pivotal in computational biology, because they allow scientists to analyze large amounts of biological data to better understand their test results, and to infer new knowledge. Yet, biomolecular annotation databases are incomplete by definition, like our knowledge of biology, and may contain errors and inconsistent information. In this context, machine-learning algorithms able to predict and prioritize new biomolecular annotations are both effective and efficient, especially if compared with the time-consuming trials of biological validation. To limit the possibility that these techniques predict obvious and trivial high-level features, and to help prioritizing their results, we introduce here a new element that can improve the accuracy and relevance of the results of an annotation prediction and prioritization pipeline. We propose a novelty indicator able to state the level of ”newness” (or ”originality”) of the annotations predicted for a specific gene to Gene Ontology terms, and to help prioritizing the most novel and interesting annotations predicted. We performed a thorough biological functional analysis of the prioritized annotations predicted with high accuracy by using this indicator and our previously proposed prediction algorithms. The relevance -
Shear Stress Modulates Gene Expression in Normal Human Dermal Fibroblasts
University of Calgary PRISM: University of Calgary's Digital Repository Graduate Studies The Vault: Electronic Theses and Dissertations 2017 Shear Stress Modulates Gene Expression in Normal Human Dermal Fibroblasts Zabinyakov, Nikita Zabinyakov, N. (2017). Shear Stress Modulates Gene Expression in Normal Human Dermal Fibroblasts (Unpublished master's thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/27775 http://hdl.handle.net/11023/3639 master thesis University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission. Downloaded from PRISM: https://prism.ucalgary.ca UNIVERSITY OF CALGARY Shear Stress Modulates Gene Expression in Normal Human Dermal Fibroblasts by Nikita Zabinyakov A THESIS SUBMITTED TO THE FACULTY OF GRADUATE STUDIES IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE GRADUATE PROGRAM IN BIOMEDICAL ENGINEERING CALGARY, ALBERTA JANUARY 2017 © Nikita Zabinyakov 2017 Abstract Applied mechanical forces, such as those resulting from fluid flow, trigger cells to change their functional behavior or phenotype. However, there is little known about how fluid flow affects fibroblasts. The hypothesis of this thesis is that dermal fibroblasts undergo significant changes of expression of differentiation genes after exposure to fluid flow (or shear stress). To test the hypothesis, human dermal fibroblasts were exposed to laminar steady fluid flow for 20 and 40 hours and RNA was collected for microarray analysis. -
Supplementary Material Computational Prediction of SARS
Supplementary_Material Computational prediction of SARS-CoV-2 encoded miRNAs and their putative host targets Sheet_1 List of potential stem-loop structures in SARS-CoV-2 genome as predicted by VMir. Rank Name Start Apex Size Score Window Count (Absolute) Direct Orientation 1 MD13 2801 2864 125 243.8 61 2 MD62 11234 11286 101 211.4 49 4 MD136 27666 27721 104 205.6 119 5 MD108 21131 21184 110 204.7 210 9 MD132 26743 26801 119 188.9 252 19 MD56 9797 9858 128 179.1 59 26 MD139 28196 28233 72 170.4 133 28 MD16 2934 2974 76 169.9 71 43 MD103 20002 20042 80 159.3 403 46 MD6 1489 1531 86 156.7 171 51 MD17 2981 3047 131 152.8 38 87 MD4 651 692 75 140.3 46 95 MD7 1810 1872 121 137.4 58 116 MD140 28217 28252 72 133.8 62 122 MD55 9712 9758 96 132.5 49 135 MD70 13171 13219 93 130.2 131 164 MD95 18782 18820 79 124.7 184 173 MD121 24086 24135 99 123.1 45 176 MD96 19046 19086 75 123.1 179 196 MD19 3197 3236 76 120.4 49 200 MD86 17048 17083 73 119.8 428 223 MD75 14534 14600 137 117 51 228 MD50 8824 8870 94 115.8 79 234 MD129 25598 25642 89 115.6 354 Reverse Orientation 6 MR61 19088 19132 88 197.8 271 10 MR72 23563 23636 148 188.8 286 11 MR11 3775 3844 136 185.1 116 12 MR94 29532 29582 94 184.6 271 15 MR43 14973 15028 109 183.9 226 27 MR14 4160 4206 89 170 241 34 MR35 11734 11792 111 164.2 37 52 MR5 1603 1652 89 152.7 118 53 MR57 18089 18132 101 152.7 139 94 MR8 2804 2864 122 137.4 38 107 MR58 18474 18508 72 134.9 237 117 MR16 4506 4540 72 133.8 311 120 MR34 10010 10048 82 132.7 245 133 MR7 2534 2578 90 130.4 75 146 MR79 24766 24808 75 127.9 59 150 MR65 21528 21576 99 127.4 83 180 MR60 19016 19049 70 122.5 72 187 MR51 16450 16482 75 121 363 190 MR80 25687 25734 96 120.6 75 198 MR64 21507 21544 70 120.3 35 206 MR41 14500 14542 84 119.2 94 218 MR84 26840 26894 108 117.6 94 Sheet_2 List of stable stem-loop structures based on MFE. -
(Q36.1;Q24) with a Concurrent Submicroscopic Del(4)(Q23q24) in an Adult with Polycythemia Vera
cancers Case Report A Novel Acquired t(2;4)(q36.1;q24) with a Concurrent Submicroscopic del(4)(q23q24) in An Adult with Polycythemia Vera Eigil Kjeldsen Cancer Cytogenetic Section, HemoDiagnostic Laboratory, Department of Hematology, Aarhus University Hospital, Tage-Hansens Gade 2, DK-8000 Aarhus C, Denmark; [email protected]; Tel.: +45-7846-7398; Fax: +45-7846-7399 Received: 6 June 2018; Accepted: 21 June 2018; Published: 25 June 2018 Abstract: Background: Polycythemia vera (PV) is a clonal myeloid stem cell disease characterized by a growth-factor independent erythroid proliferation with an inherent tendency to transform into overt acute myeloid malignancy. Approximately 95% of the PV patients harbor the JAK2V617F mutation while less than 35% of the patients harbor cytogenetic abnormalities at the time of diagnosis. Methods and Results: Here we present a JAK2V617F positive PV patient where G-banding revealed an apparently balanced t(2;4)(q35;q21), which was confirmed by 24-color karyotyping. Oligonucleotide array-based Comparative Genomic Hybridization (aCGH) analysis revealed an interstitial 5.4 Mb large deletion at 4q23q24. Locus-specific fluorescent in situ hybridization (FISH) analyses confirmed the mono-allelic 4q deletion and that it was located on der(4)t(2;4). Additional locus-specific bacterial artificial chromosome (BAC) probes and mBanding refined the breakpoint on chromosome 2. With these methods the karyotype was revised to 46,XX,t(2;4)(q36.1;q24)[18]/46,XX[7]. Conclusions: This is the first report on a PV patient associated with an acquired novel t(2;4)(q36.1;q24) and a concurrent submicroscopic deletion del(4)(q23q24). -
Novel Gene Discovery in Primary Ciliary Dyskinesia
Novel Gene Discovery in Primary Ciliary Dyskinesia Mahmoud Raafat Fassad Genetics and Genomic Medicine Programme Great Ormond Street Institute of Child Health University College London A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy University College London 1 Declaration I, Mahmoud Raafat Fassad, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. 2 Abstract Primary Ciliary Dyskinesia (PCD) is one of the ‘ciliopathies’, genetic disorders affecting either cilia structure or function. PCD is a rare recessive disease caused by defective motile cilia. Affected individuals manifest with neonatal respiratory distress, chronic wet cough, upper respiratory tract problems, progressive lung disease resulting in bronchiectasis, laterality problems including heart defects and adult infertility. Early diagnosis and management are essential for better respiratory disease prognosis. PCD is a highly genetically heterogeneous disorder with causal mutations identified in 36 genes that account for the disease in about 70% of PCD cases, suggesting that additional genes remain to be discovered. Targeted next generation sequencing was used for genetic screening of a cohort of patients with confirmed or suggestive PCD diagnosis. The use of multi-gene panel sequencing yielded a high diagnostic output (> 70%) with mutations identified in known PCD genes. Over half of these mutations were novel alleles, expanding the mutation spectrum in PCD genes. The inclusion of patients from various ethnic backgrounds revealed a striking impact of ethnicity on the composition of disease alleles uncovering a significant genetic stratification of PCD in different populations. -
From Zebrafish Heart Jogging Genes to Mouse and Human Orthologs: Using Gene Ontology to Investigate Mammalian Heart Development. [Version 2; Peer Review: 2 Approved]
F1000Research 2014, 2:242 Last updated: 22 SEP 2021 RESEARCH ARTICLE From zebrafish heart jogging genes to mouse and human orthologs: using Gene Ontology to investigate mammalian heart development. [version 2; peer review: 2 approved] Varsha K Khodiyar1, Doug Howe2, Philippa J Talmud1, Ross Breckenridge3, Ruth C Lovering 1 1Cardiovascular GO Annotation Initiative, Centre for Cardiovascular Genetics, Institute of Cardiovascular Science, University College London, London, WC1E 6JF, UK 2The Zebrafish Model Organism Database, University of Oregon, Eugene, OR, 97403-5291, USA 3Centre for Metabolism and Experimental Therapeutics, University College London, London, WC1E 6JF, UK v2 First published: 13 Nov 2013, 2:242 Open Peer Review https://doi.org/10.12688/f1000research.2-242.v1 Latest published: 10 Feb 2014, 2:242 https://doi.org/10.12688/f1000research.2-242.v2 Reviewer Status Invited Reviewers Abstract For the majority of organs in developing vertebrate embryos, left-right 1 2 asymmetry is controlled by a ciliated region; the left-right organizer node in the mouse and human, and the Kuppfer’s vesicle in the version 2 zebrafish. In the zebrafish, laterality cues from the Kuppfer’s vesicle (revision) determine asymmetry in the developing heart, the direction of ‘heart 10 Feb 2014 jogging’ and the direction of ‘heart looping’. ‘Heart jogging’ is the term given to the process by which the symmetrical zebrafish heart version 1 tube is displaced relative to the dorsal midline, with a leftward ‘jog’. 13 Nov 2013 report report Heart jogging is not considered to occur in mammals, although a leftward shift of the developing mouse caudal heart does occur prior to looping, which may be analogous to zebrafish heart jogging. -
Table S1. PCD Genes Analysed from the Multi-Gene Panel. Gene Names
Supplementary material J Med Genet Table S1. PCD genes analysed from the multi-gene panel. Gene ID Transmission electron microscopy (TEM) defects Genomic Interval # exons ARMC4 ODA chr10:28089736-28284096 22 CFAP298/C21ORF59 ODA+IDA chr21:33951107-33984578 10 CCDC103 ODA+IDA chr17:42978342-42980210 3 CCDC114 ODA chr19:48800208-48822053 13 CCDC151 ODA chr19:11531478-11546617 16 CCDC39 MT disorganised+IDA chr3:180331609-180466094 24 CCDC40 MT disorganised+IDA chr17:78010437-78073599 24 CCDC65 MT disorganised/sub-TEM defect chr12:49298095-49325285 9 CCNO Reduced cilia numbers chr5:54527178-54529376 3 DNAAF1 ODA+IDA chr16:84179021-84212037 15 DNAAF2 ODA+IDA chr14:50092235-50101892 3 DNAAF3 ODA+IDA chr19:55670405-55678041 12 DNAAF5 ODA+IDA chr7:766333-825315 13 DNAH11 Normal (sub-TEM defect) chr7:21582839-21940897 85 DNAH5 ODA chr5:13692068-13944572 79 DNAI1 ODA chr9:34458979-34520779 21 DNAI2 ODA chr17:72277761-72310380 12 DNAJB13 CP chr11:73662090-73681184 8 DNAL1 ODA chr14:74111718-74162670 8 DRC1 MT disorganised/sub-TEM defect chr2:26624833-26679410 19 DYX1C1 ODA+IDA chr15:55710208-55790552 10 GAS8 Normal (sub-TEM defect) chr16:90089105-90109778 11 HYDIN CP/sub-TEM defect chr16:70841458-71264615 90 LRRC6 ODA+IDA chr8:133584529-133687764 15 MCIDAS Reduced cilia numbers chr5:54516169-54522991 7 NME8 ODA chr7:37889844-37936719 15 OFD1 Not published chrX:13753166-13787252 24 PIH1D3 ODA+IDA chrX:106456081-106486553 6 RPGR Mixed chrX:38128854-38186645 20 RSPH1 CP chr21:43892903-43916321 9 RSPH3 CP chr6:159398545-159421033 8 RSPH4A CP chr6:116937762-116953629 6 RSPH9 CP chr6:43612811-43640212 7 SPAG1 ODA+IDA chr8:101174484-101253275 18 STK36 CP/sub-TEM defect chr2:219537528-219566757 28 TTC25 ODA chr17:40086952-40117526 11 ZMYND10 ODA+IDA chr3:50378816-50383035 12 Gene names according to HUGO Gene Nomenclature Committee.