Reln As a Candidate Gene for Autism Spectrum Disorder (Asd)
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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 -
Physical and Linkage Mapping of Mammary-Derived Expressed Sequence Tags in Cattle
Genomics 83 (2004) 148–152 www.elsevier.com/locate/ygeno Physical and linkage mapping of mammary-derived expressed sequence tags in cattle E.E. Connor,a,* T.S. Sonstegard,a J.W. Keele,b G.L. Bennett,b J.L. Williams,c R. Papworth,c C.P. Van Tassell,a and M.S. Ashwella a U.S. Beltsville Agricultural Research Center, ARS, U.S. Department of Agriculture, 10300 Baltimore Avenue, Beltsville, MD 20705, USA b U.S. Meat Animal Research Center, ARS, U.S. Department of Agriculture, P.O. Box 166, Clay Center, NE 68933-0166, USA c Roslin Institute (Edinburgh), Roslin, Midlothian EH25 9PS, Scotland, United Kingdom Received 2 June 2003; accepted 5 July 2003 Abstract This study describes the physical and linkage mapping of 42 gene-associated markers developed from mammary gland-derived expressed sequence tags to the cattle genome. Of the markers, 25 were placed on the USDA reference linkage map and 37 were positioned on the Roslin 3000-rad radiation hybrid (RH) map, with 20 assignments shared between the maps. Although no novel regions of conserved synteny between the cattle and the human genomes were identified, the coverage was extended for bovine chromosomes 3, 7, 15, and 29 compared with previously published comparative maps between human and bovine genomes. Overall, these data improve the resolution of the human–bovine comparative maps and will assist future efforts to integrate bovine RH and linkage map data. Crown Copyright D 2003 Published by Elsevier Inc. All rights reserved. Keywords: RH mapping; Linkage mapping; SNP; Cattle; EST Selection of positional candidate genes controlling eco- pig [4,5], and cattle [6], and serve as a resource for nomically important traits in cattle requires a detailed candidate gene identification. -
(P -Value<0.05, Fold Change≥1.4), 4 Vs. 0 Gy Irradiation
Table S1: Significant differentially expressed genes (P -Value<0.05, Fold Change≥1.4), 4 vs. 0 Gy irradiation Genbank Fold Change P -Value Gene Symbol Description Accession Q9F8M7_CARHY (Q9F8M7) DTDP-glucose 4,6-dehydratase (Fragment), partial (9%) 6.70 0.017399678 THC2699065 [THC2719287] 5.53 0.003379195 BC013657 BC013657 Homo sapiens cDNA clone IMAGE:4152983, partial cds. [BC013657] 5.10 0.024641735 THC2750781 Ciliary dynein heavy chain 5 (Axonemal beta dynein heavy chain 5) (HL1). 4.07 0.04353262 DNAH5 [Source:Uniprot/SWISSPROT;Acc:Q8TE73] [ENST00000382416] 3.81 0.002855909 NM_145263 SPATA18 Homo sapiens spermatogenesis associated 18 homolog (rat) (SPATA18), mRNA [NM_145263] AA418814 zw01a02.s1 Soares_NhHMPu_S1 Homo sapiens cDNA clone IMAGE:767978 3', 3.69 0.03203913 AA418814 AA418814 mRNA sequence [AA418814] AL356953 leucine-rich repeat-containing G protein-coupled receptor 6 {Homo sapiens} (exp=0; 3.63 0.0277936 THC2705989 wgp=1; cg=0), partial (4%) [THC2752981] AA484677 ne64a07.s1 NCI_CGAP_Alv1 Homo sapiens cDNA clone IMAGE:909012, mRNA 3.63 0.027098073 AA484677 AA484677 sequence [AA484677] oe06h09.s1 NCI_CGAP_Ov2 Homo sapiens cDNA clone IMAGE:1385153, mRNA sequence 3.48 0.04468495 AA837799 AA837799 [AA837799] Homo sapiens hypothetical protein LOC340109, mRNA (cDNA clone IMAGE:5578073), partial 3.27 0.031178378 BC039509 LOC643401 cds. [BC039509] Homo sapiens Fas (TNF receptor superfamily, member 6) (FAS), transcript variant 1, mRNA 3.24 0.022156298 NM_000043 FAS [NM_000043] 3.20 0.021043295 A_32_P125056 BF803942 CM2-CI0135-021100-477-g08 CI0135 Homo sapiens cDNA, mRNA sequence 3.04 0.043389246 BF803942 BF803942 [BF803942] 3.03 0.002430239 NM_015920 RPS27L Homo sapiens ribosomal protein S27-like (RPS27L), mRNA [NM_015920] Homo sapiens tumor necrosis factor receptor superfamily, member 10c, decoy without an 2.98 0.021202829 NM_003841 TNFRSF10C intracellular domain (TNFRSF10C), mRNA [NM_003841] 2.97 0.03243901 AB002384 C6orf32 Homo sapiens mRNA for KIAA0386 gene, partial cds. -
Inaugural-Dissertation Zur Erlangung Der Doktorwürde Der Naturwissenschaftlich-Mathematischen Gesamtfakultät Der Ruprecht-Kar
Inaugural-Dissertation zur Erlangung der Doktorwürde der Naturwissenschaftlich-Mathematischen Gesamtfakultät der Ruprecht-Karls-Universität Heidelberg vorgelegt von Diplom-Biochemiker Stefan Knoth Tag der mündlichen Prüfung: 25.07.2006 Titel der Arbeit: Regulation der Genexpression bei der Erythroiden Differenzierung Gutachter: Prof. Dr. Stefan Wölfl, Universität Heidelberg Prof. Dr. Katharina Pachmann, Universität Jena Prof. Dr. Jürgen Reichling Prof. Dr. Ulrich Hilgenfeldt Zusammenfassung Viele Erkrankungen des blutbildenden Systems, insbesondere Leukämien, haben ihre Ursache in einer Störung der Differenzierungvorgänge, die ausgehend von undifferenzierten Stammzellen des Knochenmarks zu allen Arten von hochspezialisierten Blutzellen führen. Bei der Chronischen Myeloischen Leukämie (CML) im Stadium der Blastenkrise kommt es zu einer unkontrollierten Vermehrung unreifer Blasten. Alle Chronischen Myeloischen Leukämien exprimieren dass Fusionsprotein BCR-ABL welches aus der Translokation t(9;22)(q34;q11) resultiert. BCR-ABL ist eine konstitutiv aktive Proteinkinase und stimuliert die Zellen zu unkontrolliertem Wachstum. Es ist bekannt, dass sich bei transformierten Zellen mit verschiedenen Substanzen wie AraC oder Butyrat die Proliferation unterdrücken und eine weitere Differenzierung induzieren lässt. Daher werden diese Substanzen oder ihre Derivate als Therapeutika eingesetzt bzw. als solche erprobt. Bei CML-Zellen geht man davon aus, dass durch die genannten Chemikalien die Differenzierung in Richtung der erythroiden Reihe stimuliert wird, da verstärkt Hämoglobine synthetisiert werden. Wegen ihrer einfachen Handhabung in Kultur wurden diese Zellsysteme in der Vergangenheit häufig als Modelle zur Untersuchung der erythroiden Differenzierung verwendet. Die therapeutikastimulierte erythroide Differenzierung von CML-Zellen ist also in zweierlei Hinsicht interessant, einerseits aus medizinischer Sicht zur Bewertung der Vorgänge im behandelten Patienten und andererseits hinsichtlich der Eignung dieser Systeme als Modelle zur Erforschung der Erythropoese. -
Ubiquitin-Dependent Regulation of the WNT Cargo Protein EVI/WLS Handelt Es Sich Um Meine Eigenständig Erbrachte Leistung
DISSERTATION submitted to the Combined Faculty of Natural Sciences and Mathematics of the Ruperto-Carola University of Heidelberg, Germany for the degree of Doctor of Natural Sciences presented by Lucie Magdalena Wolf, M.Sc. born in Nuremberg, Germany Date of oral examination: 2nd February 2021 Ubiquitin-dependent regulation of the WNT cargo protein EVI/WLS Referees: Prof. Dr. Michael Boutros apl. Prof. Dr. Viktor Umansky If you don’t think you might, you won’t. Terry Pratchett This work was accomplished from August 2015 to November 2020 under the supervision of Prof. Dr. Michael Boutros in the Division of Signalling and Functional Genomics at the German Cancer Research Center (DKFZ), Heidelberg, Germany. Contents Contents ......................................................................................................................... ix 1 Abstract ....................................................................................................................xiii 1 Zusammenfassung .................................................................................................... xv 2 Introduction ................................................................................................................ 1 2.1 The WNT signalling pathways and cancer ........................................................................ 1 2.1.1 Intercellular communication ........................................................................................ 1 2.1.2 WNT ligands are conserved morphogens ................................................................. -
Supplementary Materials and Tables a and B
SUPPLEMENTARY MATERIAL 1 Table A. Main characteristics of the subset of 23 AML patients studied by high-density arrays (subset A) WBC BM blasts MYST3- MLL Age/Gender WHO / FAB subtype Karyotype FLT3-ITD NPM status (x109/L) (%) CREBBP status 1 51 / F M4 NA 21 78 + - G A 2 28 / M M4 t(8;16)(p11;p13) 8 92 + - G G 3 53 / F M4 t(8;16)(p11;p13) 27 96 + NA G NA 4 24 / M PML-RARα / M3 t(15;17) 5 90 - - G G 5 52 / M PML-RARα / M3 t(15;17) 1.5 75 - - G G 6 31 / F PML-RARα / M3 t(15;17) 3.2 89 - - G G 7 23 / M RUNX1-RUNX1T1 / M2 t(8;21) 38 34 - + ND G 8 52 / M RUNX1-RUNX1T1 / M2 t(8;21) 8 68 - - ND G 9 40 / M RUNX1-RUNX1T1 / M2 t(8;21) 5.1 54 - - ND G 10 63 / M CBFβ-MYH11 / M4 inv(16) 297 80 - - ND G 11 63 / M CBFβ-MYH11 / M4 inv(16) 7 74 - - ND G 12 59 / M CBFβ-MYH11 / M0 t(16;16) 108 94 - - ND G 13 41 / F MLLT3-MLL / M5 t(9;11) 51 90 - + G R 14 38 / F M5 46, XX 36 79 - + G G 15 76 / M M4 46 XY, der(10) 21 90 - - G NA 16 59 / M M4 NA 29 59 - - M G 17 26 / M M5 46, XY 295 92 - + G G 18 62 / F M5 NA 67 88 - + M A 19 47 / F M5 del(11q23) 17 78 - + M G 20 50 / F M5 46, XX 61 59 - + M G 21 28 / F M5 46, XX 132 90 - + G G 22 30 / F AML-MD / M5 46, XX 6 79 - + M G 23 64 / M AML-MD / M1 46, XY 17 83 - + M G WBC: white blood cell. -
Mclean, Chelsea.Pdf
COMPUTATIONAL PREDICTION AND EXPERIMENTAL VALIDATION OF NOVEL MOUSE IMPRINTED GENES A Dissertation Presented to the Faculty of the Graduate School of Cornell University In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by Chelsea Marie McLean August 2009 © 2009 Chelsea Marie McLean COMPUTATIONAL PREDICTION AND EXPERIMENTAL VALIDATION OF NOVEL MOUSE IMPRINTED GENES Chelsea Marie McLean, Ph.D. Cornell University 2009 Epigenetic modifications, including DNA methylation and covalent modifications to histone tails, are major contributors to the regulation of gene expression. These changes are reversible, yet can be stably inherited, and may last for multiple generations without change to the underlying DNA sequence. Genomic imprinting results in expression from one of the two parental alleles and is one example of epigenetic control of gene expression. So far, 60 to 100 imprinted genes have been identified in the human and mouse genomes, respectively. Identification of additional imprinted genes has become increasingly important with the realization that imprinting defects are associated with complex disorders ranging from obesity to diabetes and behavioral disorders. Despite the importance imprinted genes play in human health, few studies have undertaken genome-wide searches for new imprinted genes. These have used empirical approaches, with some success. However, computational prediction of novel imprinted genes has recently come to the forefront. I have developed generalized linear models using data on a variety of sequence and epigenetic features within a training set of known imprinted genes. The resulting models were used to predict novel imprinted genes in the mouse genome. After imposing a stringency threshold, I compiled an initial candidate list of 155 genes. -
Figure S1. Reverse Transcription‑Quantitative PCR Analysis of ETV5 Mrna Expression Levels in Parental and ETV5 Stable Transfectants
Figure S1. Reverse transcription‑quantitative PCR analysis of ETV5 mRNA expression levels in parental and ETV5 stable transfectants. (A) Hec1a and Hec1a‑ETV5 EC cell lines; (B) Ishikawa and Ishikawa‑ETV5 EC cell lines. **P<0.005, unpaired Student's t‑test. EC, endometrial cancer; ETV5, ETS variant transcription factor 5. Figure S2. Survival analysis of sample clusters 1‑4. Kaplan Meier graphs for (A) recurrence‑free and (B) overall survival. Survival curves were constructed using the Kaplan‑Meier method, and differences between sample cluster curves were analyzed by log‑rank test. Figure S3. ROC analysis of hub genes. For each gene, ROC curve (left) and mRNA expression levels (right) in control (n=35) and tumor (n=545) samples from The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer cohort are shown. mRNA levels are expressed as Log2(x+1), where ‘x’ is the RSEM normalized expression value. ROC, receiver operating characteristic. Table SI. Clinicopathological characteristics of the GSE17025 dataset. Characteristic n % Atrophic endometrium 12 (postmenopausal) (Control group) Tumor stage I 91 100 Histology Endometrioid adenocarcinoma 79 86.81 Papillary serous 12 13.19 Histological grade Grade 1 30 32.97 Grade 2 36 39.56 Grade 3 25 27.47 Myometrial invasiona Superficial (<50%) 67 74.44 Deep (>50%) 23 25.56 aMyometrial invasion information was available for 90 of 91 tumor samples. Table SII. Clinicopathological characteristics of The Cancer Genome Atlas Uterine Corpus Endometrioid Cancer dataset. Characteristic n % Solid tissue normal 16 Tumor samples Stagea I 226 68.278 II 19 5.740 III 70 21.148 IV 16 4.834 Histology Endometrioid 271 81.381 Mixed 10 3.003 Serous 52 15.616 Histological grade Grade 1 78 23.423 Grade 2 91 27.327 Grade 3 164 49.249 Molecular subtypeb POLE 17 7.328 MSI 65 28.017 CN Low 90 38.793 CN High 60 25.862 CN, copy number; MSI, microsatellite instability; POLE, DNA polymerase ε. -
T-Cell Development of Resistance to Apoptosis Is Driven by a Metabolic Shift in Carbon Source and Altered Activation of Death Pathways
Cell Death and Differentiation (2016) 23, 889–902 & 2016 Macmillan Publishers Limited All rights reserved 1350-9047/16 www.nature.com/cdd T-cell development of resistance to apoptosis is driven by a metabolic shift in carbon source and altered activation of death pathways CD Bortner1, AB Scoltock1, DW Cain1 and JA Cidlowski*,1 We developed a model system to investigate apoptotic resistance in T cells using osmotic stress (OS) to drive selection of death- resistant cells. Exposure of S49 (Neo) T cells to multiple rounds of OS followed by recovery of surviving cells resulted in the selection of a population of T cells (S49 (OS 4–25)) that failed to die in response to a variety of intrinsic apoptotic stimuli including acute OS, but remained sensitive to extrinsic apoptotic initiators. Genome-wide microarray analysis comparing the S49 (OS 4–25) with the parent S49 (Neo) cells revealed over 8500 differentially regulated genes, with almost 90% of those identified being repressed. Surprisingly, our data revealed that apoptotic resistance is not associated with expected changes in pro- or antiapoptotic Bcl-2 family member genes. Rather, these cells lack several characteristics associated with the initial signaling or activation of the intrinsic apoptosis pathway, including failure to increase mitochondrial-derived reactive oxygen species, failure to increase intracellular calcium, failure to deplete glutathione, failure to release cytochrome c from the mitochondria, along with a lack of induced caspase activity. The S49 (OS 4–25) cells exhibit metabolic characteristics indicative of the Warburg effect, and, despite numerous changes in mitochondria gene expression, the mitochondria have a normal metabolic capacity. -
Proteomic Analysis of Monolayer-Integrated Proteins on Lipid Droplets Identifies Amphipathic Interfacial Α-Helical Membrane Anchors
Proteomic analysis of monolayer-integrated proteins on lipid droplets identifies amphipathic interfacial α-helical membrane anchors Camille I. Patakia, João Rodriguesb, Lichao Zhangc, Junyang Qiand, Bradley Efrond, Trevor Hastied, Joshua E. Eliasc, Michael Levittb, and Ron R. Kopitoe,1 aDepartment of Biochemistry, Stanford University, Stanford, CA 94305; bDepartment of Structural Biology, Stanford University, Stanford, CA 94305; cDepartment of Chemical and Systems Biology, Stanford University, Stanford, CA 94305; dDepartment of Statistics, Stanford University, Stanford, CA 94305; and eDepartment of Biology, Stanford University, Stanford, CA 94305 Edited by Jennifer Lippincott-Schwartz, Howard Hughes Medical Institute, Ashburn, VA, and approved July 23, 2018 (received for review May 9, 2018) Despite not spanning phospholipid bilayers, monotopic integral The first step in understanding the structural diversity of proteins (MIPs) play critical roles in organizing biochemical reac- monotopic HMDs is to identify a sufficiently large set of proteins tions on membrane surfaces. Defining the structural basis by with unequivocal monotopic topology. In this study, we exploited which these proteins are anchored to membranes has been the fact that lipid droplets (LDs) are enveloped by phospholipid hampered by the paucity of unambiguously identified MIPs and a monolayers that separate a highly hydrophobic lipid core from lack of computational tools that accurately distinguish monolayer- the aqueous cytoplasm (8). Because TMDs are flanked on both integrating motifs from bilayer-spanning transmembrane domains ends by soluble, hydrophilic domains, bilayer-spanning proteins (TMDs). We used quantitative proteomics and statistical modeling are strongly disfavored from integrating into the monolayer to identify 87 high-confidence candidate MIPs in lipid droplets, membranes of LDs. -
Pathogenic Mechanisms and Clinical Implications of Congenital Neutropenia Syndromes
REVIEW CURRENT OPINION Pathogenic mechanisms and clinical implications of congenital neutropenia syndromes Fabian Hauck and Christoph Klein Purpose of review The purpose of this review is to summarize pathogenic mechanisms and clinical implications of the most illustrative genetic entities of congenital neutropenia syndromes. Recent findings Congenital neutropenia comprise monogenetic entities with or without additional immunologic and extrahaematopoietic syndromatic features. Continuous careful explorations of known entities such as ELANE, GFI1, HAX1, G6PC3 deficiency and XLN help to define principles controlling differentiation and function of neutrophil granulocytes. Furthermore, the identification of novel genetic defects associated with congenital neutropenia, such as VPS45 deficiency, broadens our understanding of neutrophil biology. Pathogenic mechanisms imply protein and vesicle mistrafficking, endoplasmic reticulum stress, the unfolded protein response, destabilization of the mitochondrial membrane potential, disturbed energy metabolism, dysglycosylation and deregulated actin polymerization. Summary Advanced genetic and biochemical techniques have helped to expand our knowledge of congenital neutropenia syndromes. Known and novel genetic entities shed light on fundamental biological processes important for the homeostatis and functioning not only of the neutrophil granulocyte but as well of the entire haematopoietic system. Furthermore, treatment decisions become more tailored and might pave the road towards personalized molecular -
1 Novel Expression Signatures Identified by Transcriptional Analysis
ARD Online First, published on October 7, 2009 as 10.1136/ard.2009.108043 Ann Rheum Dis: first published as 10.1136/ard.2009.108043 on 7 October 2009. Downloaded from Novel expression signatures identified by transcriptional analysis of separated leukocyte subsets in SLE and vasculitis 1Paul A Lyons, 1Eoin F McKinney, 1Tim F Rayner, 1Alexander Hatton, 1Hayley B Woffendin, 1Maria Koukoulaki, 2Thomas C Freeman, 1David RW Jayne, 1Afzal N Chaudhry, and 1Kenneth GC Smith. 1Cambridge Institute for Medical Research and Department of Medicine, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK 2Roslin Institute, University of Edinburgh, Roslin, Midlothian, EH25 9PS, UK Correspondence should be addressed to Dr Paul Lyons or Prof Kenneth Smith, Department of Medicine, Cambridge Institute for Medical Research, Addenbrooke’s Hospital, Hills Road, Cambridge, CB2 0XY, UK. Telephone: +44 1223 762642, Fax: +44 1223 762640, E-mail: [email protected] or [email protected] Key words: Gene expression, autoimmune disease, SLE, vasculitis Word count: 2,906 The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Annals of the Rheumatic Diseases and any other BMJPGL products to exploit all subsidiary rights, as set out in their licence (http://ard.bmj.com/ifora/licence.pdf). http://ard.bmj.com/ on September 29, 2021 by guest. Protected copyright. 1 Copyright Article author (or their employer) 2009.