The Interaction of DNA Repair Factors ASCC2 and ASCC3 Is Affected By
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Hypopituitarism May Be an Additional Feature of SIM1 and POU3F2 Containing 6Q16 Deletions in Children with Early Onset Obesity
Open Access Journal of Pediatric Endocrinology Case Report Hypopituitarism may be an Additional Feature of SIM1 and POU3F2 Containing 6q16 Deletions in Children with Early Onset Obesity Rutteman B1, De Rademaeker M2, Gies I1, Van den Bogaert A2, Zeevaert R1, Vanbesien J1 and De Abstract Schepper J1* Over the past decades, 6q16 deletions have become recognized as a 1Department of Pediatric Endocrinology, UZ Brussel, frequent cause of the Prader-Willi-like syndrome. Involvement of SIM1 in the Belgium deletion has been linked to the development of obesity. Although SIM1 together 2Department of Genetics, UZ Brussel, Belgium with POU3F2, which is located close to the SIM1 locus, are involved in pituitary *Corresponding author: De Schepper J, Department development and function, pituitary dysfunction has not been reported frequently of Pediatric Endocrinology, UZ Brussel, Belgium in cases of 6q16.1q16.3 deletion involving both genes. Here we report on a case of a girl with typical Prader-Willi-like symptoms including early-onset Received: December 23, 2016; Accepted: February 21, hyperphagic obesity, hypotonia, short hands and feet and neuro-psychomotor 2017; Published: February 22, 2017 development delay. Furthermore, she suffered from central diabetes insipidus, central hypothyroidism and hypocortisolism. Her genetic defect is a 6q16.1q16.3 deletion, including SIM1 and POU3F2. We recommend searching for a 6q16 deletion in children with early onset hyperphagic obesity associated with biological signs of hypopituitarism and/or polyuria-polydipsia syndrome. The finding of a combined SIM1 and POU3F2 deletion should prompt monitoring for the development of hypopituitarism, if not already present at diagnosis. Keywords: 6q16 deletion; SIM1; POU3F2; Prader-Willi-like syndrome; Hypopituitarism Introduction insipidus and of some specific pituitary hormone deficiencies in children with a combined SIM1 and POU3F2 deficiency. -
S41467-020-18249-3.Pdf
ARTICLE https://doi.org/10.1038/s41467-020-18249-3 OPEN Pharmacologically reversible zonation-dependent endothelial cell transcriptomic changes with neurodegenerative disease associations in the aged brain Lei Zhao1,2,17, Zhongqi Li 1,2,17, Joaquim S. L. Vong2,3,17, Xinyi Chen1,2, Hei-Ming Lai1,2,4,5,6, Leo Y. C. Yan1,2, Junzhe Huang1,2, Samuel K. H. Sy1,2,7, Xiaoyu Tian 8, Yu Huang 8, Ho Yin Edwin Chan5,9, Hon-Cheong So6,8, ✉ ✉ Wai-Lung Ng 10, Yamei Tang11, Wei-Jye Lin12,13, Vincent C. T. Mok1,5,6,14,15 &HoKo 1,2,4,5,6,8,14,16 1234567890():,; The molecular signatures of cells in the brain have been revealed in unprecedented detail, yet the ageing-associated genome-wide expression changes that may contribute to neurovas- cular dysfunction in neurodegenerative diseases remain elusive. Here, we report zonation- dependent transcriptomic changes in aged mouse brain endothelial cells (ECs), which pro- minently implicate altered immune/cytokine signaling in ECs of all vascular segments, and functional changes impacting the blood–brain barrier (BBB) and glucose/energy metabolism especially in capillary ECs (capECs). An overrepresentation of Alzheimer disease (AD) GWAS genes is evident among the human orthologs of the differentially expressed genes of aged capECs, while comparative analysis revealed a subset of concordantly downregulated, functionally important genes in human AD brains. Treatment with exenatide, a glucagon-like peptide-1 receptor agonist, strongly reverses aged mouse brain EC transcriptomic changes and BBB leakage, with associated attenuation of microglial priming. We thus revealed tran- scriptomic alterations underlying brain EC ageing that are complex yet pharmacologically reversible. -
Association of Gene Ontology Categories with Decay Rate for Hepg2 Experiments These Tables Show Details for All Gene Ontology Categories
Supplementary Table 1: Association of Gene Ontology Categories with Decay Rate for HepG2 Experiments These tables show details for all Gene Ontology categories. Inferences for manual classification scheme shown at the bottom. Those categories used in Figure 1A are highlighted in bold. Standard Deviations are shown in parentheses. P-values less than 1E-20 are indicated with a "0". Rate r (hour^-1) Half-life < 2hr. Decay % GO Number Category Name Probe Sets Group Non-Group Distribution p-value In-Group Non-Group Representation p-value GO:0006350 transcription 1523 0.221 (0.009) 0.127 (0.002) FASTER 0 13.1 (0.4) 4.5 (0.1) OVER 0 GO:0006351 transcription, DNA-dependent 1498 0.220 (0.009) 0.127 (0.002) FASTER 0 13.0 (0.4) 4.5 (0.1) OVER 0 GO:0006355 regulation of transcription, DNA-dependent 1163 0.230 (0.011) 0.128 (0.002) FASTER 5.00E-21 14.2 (0.5) 4.6 (0.1) OVER 0 GO:0006366 transcription from Pol II promoter 845 0.225 (0.012) 0.130 (0.002) FASTER 1.88E-14 13.0 (0.5) 4.8 (0.1) OVER 0 GO:0006139 nucleobase, nucleoside, nucleotide and nucleic acid metabolism3004 0.173 (0.006) 0.127 (0.002) FASTER 1.28E-12 8.4 (0.2) 4.5 (0.1) OVER 0 GO:0006357 regulation of transcription from Pol II promoter 487 0.231 (0.016) 0.132 (0.002) FASTER 6.05E-10 13.5 (0.6) 4.9 (0.1) OVER 0 GO:0008283 cell proliferation 625 0.189 (0.014) 0.132 (0.002) FASTER 1.95E-05 10.1 (0.6) 5.0 (0.1) OVER 1.50E-20 GO:0006513 monoubiquitination 36 0.305 (0.049) 0.134 (0.002) FASTER 2.69E-04 25.4 (4.4) 5.1 (0.1) OVER 2.04E-06 GO:0007050 cell cycle arrest 57 0.311 (0.054) 0.133 (0.002) -
Follow-Up of Loci from the International Genomics of Alzheimer’S Disease Project Identifies TRIP4 As a Novel Susceptibility Gene
OPEN Citation: Transl Psychiatry (2014) 4, e358; doi:10.1038/tp.2014.2 © 2014 Macmillan Publishers Limited All rights reserved 2158-3188/14 www.nature.com/tp ORIGINAL ARTICLE Follow-up of loci from the International Genomics of Alzheimer’s Disease Project identifies TRIP4 as a novel susceptibility gene A Ruiz1,32, S Heilmann2,3,32, T Becker4,5,32, I Hernández1, H Wagner6, M Thelen6, A Mauleón1, M Rosende-Roca1, C Bellenguez7,8,9, JC Bis10, D Harold11, A Gerrish11, R Sims11, O Sotolongo-Grau1, A Espinosa1, M Alegret1, JL Arrieta12, A Lacour4, M Leber4, J Becker6, A Lafuente1, S Ruiz1, L Vargas1, O Rodríguez1, G Ortega1, M-A Dominguez1, IGAP33, R Mayeux13,14, JL Haines15,16, MA Pericak-Vance17,18, LA Farrer19,20,21,22,23, GD Schellenberg24, V Chouraki23, LJ Launer25, C van Duijn26,27,28, S Seshadri23, C Antúnez29, MM Breteler4, M Serrano-Ríos30, F Jessen4,6, L Tárraga1, MM Nöthen2,3, W Maier4,6, M Boada1,31 and A Ramírez2,6 To follow-up loci discovered by the International Genomics of Alzheimer’s Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (Fundació ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P = 0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer’s disease risk (odds ratio = 1.31; confidence interval 95% (1.19–1.44); P = 9.74 × 10−9). -
The Interaction of DNA Repair Factors ASCC2 and ASCC3 Is Affected by Somatic Cancer Mutations
ARTICLE https://doi.org/10.1038/s41467-020-19221-x OPEN The interaction of DNA repair factors ASCC2 and ASCC3 is affected by somatic cancer mutations Junqiao Jia 1, Eva Absmeier1,5, Nicole Holton1, Agnieszka J. Pietrzyk-Brzezinska1,6, Philipp Hackert2, ✉ Katherine E. Bohnsack 2, Markus T. Bohnsack2,3 & Markus C. Wahl 1,4 The ASCC3 subunit of the activating signal co-integrator complex is a dual-cassette Ski2-like nucleic acid helicase that provides single-stranded DNA for alkylation damage repair by the 1234567890():,; α-ketoglutarate-dependent dioxygenase AlkBH3. Other ASCC components integrate ASCC3/ AlkBH3 into a complex DNA repair pathway. We mapped and structurally analyzed inter- acting ASCC2 and ASCC3 regions. The ASCC3 fragment comprises a central helical domain and terminal, extended arms that clasp the compact ASCC2 unit. ASCC2–ASCC3 interfaces are evolutionarily highly conserved and comprise a large number of residues affected by somatic cancer mutations. We quantified contributions of protein regions to the ASCC2–ASCC3 interaction, observing that changes found in cancers lead to reduced ASCC2–ASCC3 affinity. Functional dissection of ASCC3 revealed similar organization and regulation as in the spliceosomal RNA helicase Brr2. Our results delineate functional regions in an important DNA repair complex and suggest possible molecular disease principles. 1 Laboratory of Structural Biochemistry, Freie Universität Berlin, D-14195 Berlin, Germany. 2 Department of Molecular Biology, University Medical Centre Göttingen, Göttingen, Germany. 3 Göttingen Center for Molecular Biosciences, Georg-August-Universität, Göttingen, Germany. 4 Helmholtz-Zentrum Berlin für Materialien und Energie, Macromolecular Crystallography, D-12489 Berlin, Germany. 5Present address: MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, UK. -
Supplementary Information
Supplementary Information Table S1. Gene Ontology analysis of affected biological processes/pathways/themes in H1 hESCs based on sets of statistically significant differentially expressed genes. Exposures Overrepresented Categories (Upregulation) EASE Score Negative regulation of cell differentiation 0.0049 Lipid biosynthetic process 0.015 Negative regulation of cell proliferation 0.02 5 cGy, 2 h Transcription factor binding 0.037 Regulation of apoptosis 0.038 Positive regulation of anti-apoptosis 0.048 P53 signaling pathway 4.2 × 10−10 Positive regulation of apoptosis 7.5 × 10−8 Response to DNA damage stimulus 1.5 × 10−6 Cellular response to stress 9.6 × 10−6 1 Gy, 2 h Negative regulation of cell proliferation 9.8 × 10−6 Cell cycle arrest 7.0 × 10−4 Negative regulation of cell differentiation 1.5 × 10−3 Regulation of protein kinase activity 0.011 I-kappaB kinase/NF-kappaB cascade 0.025 Metallothionein superfamily 9.9 × 10−18 Induction of apoptosis 8.8 × 10−5 DNA damage response 2.6 × 10−4 1 Gy, 16 h Positive regulation of anti-apoptosis 0.001 Positive regulation of cell death 0.005 Cellular response to stress 0.012 Exposures Overrepresented Categories (Downregulation) EASE Score Alternative splicing 0.016 1 Gy, 2 h Chromatin organization 0.020 Chromatin assembly 2.0 × 10−6 Cholesterol biosynthesis 5.1 × 10−5 Macromolecular complex assembly 9.3 × 10−4 1 Gy, 16 h PPAR signaling pathway 0.007 Hemopoietic organ development 0.033 Immune system development 0.040 S2 Table S2. Gene Ontology analysis of affected biological processes/pathways/themes in H7 based on sets of statistically significant differentially expressed genes. -
Mouse Trip4 Conditional Knockout Project (CRISPR/Cas9)
https://www.alphaknockout.com Mouse Trip4 Conditional Knockout Project (CRISPR/Cas9) Objective: To create a Trip4 conditional knockout Mouse model (C57BL/6J) by CRISPR/Cas-mediated genome engineering. Strategy summary: The Trip4 gene (NCBI Reference Sequence: NM_019797 ; Ensembl: ENSMUSG00000032386 ) is located on Mouse chromosome 9. 16 exons are identified, with the ATG start codon in exon 4 and the TGA stop codon in exon 16 (Transcript: ENSMUST00000119245). Exon 5 will be selected as conditional knockout region (cKO region). Deletion of this region should result in the loss of function of the Mouse Trip4 gene. To engineer the targeting vector, homologous arms and cKO region will be generated by PCR using BAC clone RP23-363H13 as template. Cas9, gRNA and targeting vector will be co-injected into fertilized eggs for cKO Mouse production. The pups will be genotyped by PCR followed by sequencing analysis. Note: Exon 5 starts from about 5.85% of the coding region. The knockout of Exon 5 will result in frameshift of the gene. The size of intron 4 for 5'-loxP site insertion: 3867 bp, and the size of intron 5 for 3'-loxP site insertion: 1682 bp. The size of effective cKO region: ~670 bp. The cKO region does not have any other known gene. Page 1 of 8 https://www.alphaknockout.com Overview of the Targeting Strategy Wildtype allele gRNA region 5' gRNA region 3' 1 5 6 16 Targeting vector Targeted allele Constitutive KO allele (After Cre recombination) Legends Exon of mouse Trip4 Homology arm cKO region loxP site Page 2 of 8 https://www.alphaknockout.com Overview of the Dot Plot Window size: 10 bp Forward Reverse Complement Sequence 12 Note: The sequence of homologous arms and cKO region is aligned with itself to determine if there are tandem repeats. -
Multiomic Analysis of the UV-Induced DNA Damage Response
Resource Multiomic Analysis of the UV-Induced DNA Damage Response Graphical Abstract Authors Stefan Boeing, Laura Williamson, Vesela Encheva, ..., Michael Howell, Ambrosius P. Snijders, Jesper Q. Svejstrup Correspondence [email protected] In Brief Boeing et al. investigate the UV-induced DNA damage response by combining a range of proteomic and genomic screens. A function in this response for the melanoma driver STK19 as well as a number of other factors are uncovered. Highlights d A multiomic screening approach examines the UV-induced DNA damage response d Multiple factors are connected to the transcription-related DNA damage response d Melanoma gene STK19 is required for a normal DNA damage response Boeing et al., 2016, Cell Reports 15, 1597–1610 May 17, 2016 ª 2016 The Author(s) http://dx.doi.org/10.1016/j.celrep.2016.04.047 Cell Reports Resource Multiomic Analysis of the UV-Induced DNA Damage Response Stefan Boeing,1,5 Laura Williamson,1 Vesela Encheva,2 Ilaria Gori,3 Rebecca E. Saunders,3 Rachael Instrell,3 Ozan Aygun,€ 1,7 Marta Rodriguez-Martinez,1 Juston C. Weems,4 Gavin P. Kelly,5 Joan W. Conaway,4,6 Ronald C. Conaway,4,6 Aengus Stewart,5 Michael Howell,3 Ambrosius P. Snijders,2 and Jesper Q. Svejstrup1,* 1Mechanisms of Transcription Laboratory, the Francis Crick Institute, Clare Hall Laboratories, South Mimms EN6 3LD, UK 2Protein Analysis and Proteomics Laboratory, the Francis Crick Institute, Clare Hall Laboratories, South Mimms EN6 3LD, UK 3High Throughput Screening Laboratory, the Francis Crick Institute, 44 Lincoln’s -
The Human Gene Connectome As a Map of Short Cuts for Morbid Allele Discovery
The human gene connectome as a map of short cuts for morbid allele discovery Yuval Itana,1, Shen-Ying Zhanga,b, Guillaume Vogta,b, Avinash Abhyankara, Melina Hermana, Patrick Nitschkec, Dror Friedd, Lluis Quintana-Murcie, Laurent Abela,b, and Jean-Laurent Casanovaa,b,f aSt. Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, The Rockefeller University, New York, NY 10065; bLaboratory of Human Genetics of Infectious Diseases, Necker Branch, Paris Descartes University, Institut National de la Santé et de la Recherche Médicale U980, Necker Medical School, 75015 Paris, France; cPlateforme Bioinformatique, Université Paris Descartes, 75116 Paris, France; dDepartment of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel; eUnit of Human Evolutionary Genetics, Centre National de la Recherche Scientifique, Unité de Recherche Associée 3012, Institut Pasteur, F-75015 Paris, France; and fPediatric Immunology-Hematology Unit, Necker Hospital for Sick Children, 75015 Paris, France Edited* by Bruce Beutler, University of Texas Southwestern Medical Center, Dallas, TX, and approved February 15, 2013 (received for review October 19, 2012) High-throughput genomic data reveal thousands of gene variants to detect a single mutated gene, with the other polymorphic genes per patient, and it is often difficult to determine which of these being of less interest. This goes some way to explaining why, variants underlies disease in a given individual. However, at the despite the abundance of NGS data, the discovery of disease- population level, there may be some degree of phenotypic homo- causing alleles from such data remains somewhat limited. geneity, with alterations of specific physiological pathways under- We developed the human gene connectome (HGC) to over- come this problem. -
Systems Biology Evaluation of Immune Responses Induced by Human Host Defence Peptide LL-37 in Mononuclear Cellsw
PAPER www.rsc.org/molecularbiosystems | Molecular BioSystems Systems biology evaluation of immune responses induced by human host defence peptide LL-37 in mononuclear cellsw Neeloffer Mookherjee,za Pamela Hamill,a Jennifer Gardy,a Darren Blimkie,b Reza Falsafi,a Avinash Chikatamarla,a David J. Arenillas,c Silvana Doria,a Tobias R. Kollmannb and Robert E. W. Hancock*a Received 7th August 2008, Accepted 29th January 2009 First published as an Advance Article on the web 19th March 2009 DOI: 10.1039/b813787k The immune system is very complex, it involves the integrated regulation and expression of hundreds of proteins. To understand in greater detail how the human host defence immunomodulatory peptide LL-37 interacts with innate immunity, a systems approach was pursued. Polychromatic flow cytometry was employed to demonstrate that within human peripheral blood mononuclear cells, CD14+ monocytes, myeloid and plasmocytoid dendritic cells and T- and B-lymphocytes, all responded to LL-37, with the differential production of intracellular cytokines. Microarray analyses with CD14+ monocytes indicated the differential expression of 475 genes in response to stimulation with LL-37. To understand this complex response, bioinformatic interrogation, using InnateDB, of the gene ontology, signalling pathways and transcription factor binding sites was undertaken. Activation of the IkBa/NFkB, mitogen- activated protein kinases p38, ERK1/2 and JNK, and PI3K signalling pathways in response to LL-37 was demonstrated by pathway and ontology over-representation analyses, and confirmed experimentally by inhibitor studies. Computational analysis of the predicted transcription factor binding sites upstream of the genes that were regulated by LL-37 predicted the involvement of several transcription factors including NFkB and five novel factors, AP-1, AP-2, SP-1, E2F1, and EGR, which were experimentally confirmed to respond to LL-37 by performing transcription factor array studies on nuclear extracts from LL-37 treated mononuclear cells. -
Development of Novel Analysis and Data Integration Systems to Understand Human Gene Regulation
Development of novel analysis and data integration systems to understand human gene regulation Dissertation zur Erlangung des Doktorgrades Dr. rer. nat. der Fakult¨atf¨urMathematik und Informatik der Georg-August-Universit¨atG¨ottingen im PhD Programme in Computer Science (PCS) der Georg-August University School of Science (GAUSS) vorgelegt von Raza-Ur Rahman aus Pakistan G¨ottingen,April 2018 Prof. Dr. Stefan Bonn, Zentrum f¨urMolekulare Neurobiologie (ZMNH), Betreuungsausschuss: Institut f¨urMedizinische Systembiologie, Hamburg Prof. Dr. Tim Beißbarth, Institut f¨urMedizinische Statistik, Universit¨atsmedizin, Georg-August Universit¨at,G¨ottingen Prof. Dr. Burkhard Morgenstern, Institut f¨urMikrobiologie und Genetik Abtl. Bioinformatik, Georg-August Universit¨at,G¨ottingen Pr¨ufungskommission: Prof. Dr. Stefan Bonn, Zentrum f¨urMolekulare Neurobiologie (ZMNH), Referent: Institut f¨urMedizinische Systembiologie, Hamburg Prof. Dr. Tim Beißbarth, Institut f¨urMedizinische Statistik, Universit¨atsmedizin, Korreferent: Georg-August Universit¨at,G¨ottingen Prof. Dr. Burkhard Morgenstern, Weitere Mitglieder Institut f¨urMikrobiologie und Genetik Abtl. Bioinformatik, der Pr¨ufungskommission: Georg-August Universit¨at,G¨ottingen Prof. Dr. Carsten Damm, Institut f¨urInformatik, Georg-August Universit¨at,G¨ottingen Prof. Dr. Florentin W¨org¨otter, Physikalisches Institut Biophysik, Georg-August-Universit¨at,G¨ottingen Prof. Dr. Stephan Waack, Institut f¨urInformatik, Georg-August Universit¨at,G¨ottingen Tag der m¨undlichen Pr¨ufung: der 30. M¨arz2018 -
A Genomic Approach to Delineating the Occurrence of Scoliosis in Arthrogryposis Multiplex Congenita
G C A T T A C G G C A T genes Article A Genomic Approach to Delineating the Occurrence of Scoliosis in Arthrogryposis Multiplex Congenita Xenia Latypova 1, Stefan Giovanni Creadore 2, Noémi Dahan-Oliel 3,4, Anxhela Gjyshi Gustafson 2, Steven Wei-Hung Hwang 5, Tanya Bedard 6, Kamran Shazand 2, Harold J. P. van Bosse 5 , Philip F. Giampietro 7,* and Klaus Dieterich 8,* 1 Grenoble Institut Neurosciences, Université Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, 38000 Grenoble, France; [email protected] 2 Shriners Hospitals for Children Headquarters, Tampa, FL 33607, USA; [email protected] (S.G.C.); [email protected] (A.G.G.); [email protected] (K.S.) 3 Shriners Hospitals for Children, Montreal, QC H4A 0A9, Canada; [email protected] 4 School of Physical & Occupational Therapy, Faculty of Medicine and Health Sciences, McGill University, Montreal, QC H3G 2M1, Canada 5 Shriners Hospitals for Children, Philadelphia, PA 19140, USA; [email protected] (S.W.-H.H.); [email protected] (H.J.P.v.B.) 6 Alberta Congenital Anomalies Surveillance System, Alberta Health Services, Edmonton, AB T5J 3E4, Canada; [email protected] 7 Department of Pediatrics, University of Illinois-Chicago, Chicago, IL 60607, USA 8 Institut of Advanced Biosciences, Université Grenoble Alpes, Inserm, U1209, CHU Grenoble Alpes, 38000 Grenoble, France * Correspondence: [email protected] (P.F.G.); [email protected] (K.D.) Citation: Latypova, X.; Creadore, S.G.; Dahan-Oliel, N.; Gustafson, Abstract: Arthrogryposis multiplex congenita (AMC) describes a group of conditions characterized A.G.; Wei-Hung Hwang, S.; Bedard, by the presence of non-progressive congenital contractures in multiple body areas.