Epigenetic Modifications to Cytosine and Alzheimer's Disease
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
FLNC Pathogenic Variants in Patients with Cardiomyopathies
FLNC pathogenic variants in patients with cardiomyopathies: Prevalence and genotype-phenotype correlations Flavie Ader, Pascal de Groote, Patricia Réant, Caroline Rooryck-Thambo, Delphine Dupin-Deguine, Caroline Rambaud, Diala Khraiche, Claire Perret, Jean-François Pruny, Michèle Mathieu-dramard, et al. To cite this version: Flavie Ader, Pascal de Groote, Patricia Réant, Caroline Rooryck-Thambo, Delphine Dupin-Deguine, et al.. FLNC pathogenic variants in patients with cardiomyopathies: Prevalence and genotype-phenotype correlations. Clinical Genetics, Wiley, 2019, 96 (4), pp.317-329. 10.1111/cge.13594. hal-02268422 HAL Id: hal-02268422 https://hal-normandie-univ.archives-ouvertes.fr/hal-02268422 Submitted on 29 Jun 2020 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. FLNC pathogenic variants in patients with cardiomyopathies Prevalence and genotype-phenotype correlations Running Title : FLNC variants genotype-phenotype correlation Flavie Ader1,2,3, Pascal De Groote4, Patricia Réant5, Caroline Rooryck-Thambo6, Delphine Dupin-Deguine7, Caroline Rambaud8, Diala Khraiche9, Claire Perret2, Jean Francois Pruny10, Michèle Mathieu Dramard11, Marion Gérard12, Yann Troadec12, Laurent Gouya13, Xavier Jeunemaitre14, Lionel Van Maldergem15, Albert Hagège16, Eric Villard2, Philippe Charron2, 10, Pascale Richard1, 2, 10. Conflict of interest statement: none declared for each author 1. -
Evolution of Multiple Cell Clones Over a 29-Year Period of a CLL Patient
ARTICLE Received 11 May 2016 | Accepted 1 Nov 2016 | Published 16 Dec 2016 DOI: 10.1038/ncomms13765 OPEN Evolution of multiple cell clones over a 29-year period of a CLL patient Zhikun Zhao1,2,3,*, Lynn Goldin4,*, Shiping Liu1,5,*, Liang Wu1,*, Weiyin Zhou6,*, Hong Lou6,*, Qichao Yu1,7, Shirley X. Tsang8, Miaomiao Jiang1,3, Fuqiang Li1, MaryLou McMaster4, Yang Li1, Xinxin Lin1, Zhifeng Wang1, Liqin Xu1, Gerald Marti9, Guibo Li1,10,KuiWu1,10, Meredith Yeager6, Huanming Yang1,11, Xun Xu1,**, Stephen J. Chanock4,**, Bo Li1,**, Yong Hou1,10,**, Neil Caporaso4,** & Michael Dean1,4,** Chronic lymphocytic leukaemia (CLL) is a frequent B-cell malignancy, characterized by recurrent somatic chromosome alterations and a low level of point mutations. Here we present single-nucleotide polymorphism microarray analyses of a single CLL patient over 29 years of observation and treatment, and transcriptome and whole-genome sequencing at selected time points. We identify chromosome alterations 13q14 À ,6qÀ and 12q þ in early cell clones, elimination of clonal populations following therapy, and subsequent appearance of a clone containing trisomy 12 and chromosome 10 copy-neutral loss of heterogeneity that marks a major population dominant at death. Serial single-cell RNA sequencing reveals an expression pattern with high FOS, JUN and KLF4 at disease acceleration, which resolves following therapy, but reoccurs following relapse and death. Transcriptome evolution indicates complex changes in expression occur over time. In conclusion, CLL can evolve gradually during indolent phases, and undergo rapid changes following therapy. 1 BGI-Shenzhen, Shenzhen 518083, China. 2 State Key Laboratory of Bioelectronics, Southeast University, Nanjing 210096, China. -
A Mutation Update for the FLNC Gene in Myopathies and Cardiomyopathies
Received: 20 December 2019 | Revised: 12 February 2020 | Accepted: 25 February 2020 DOI: 10.1002/humu.24004 MUTATION UPDATE A mutation update for the FLNC gene in myopathies and cardiomyopathies Job A. J. Verdonschot1,2 | Els K. Vanhoutte1 | Godelieve R. F. Claes1 | Apollonia T. J. M. Helderman‐van den Enden1 | Janneke G. J. Hoeijmakers3 | Debby M. E. I. Hellebrekers1 | Amber de Haan1 | Imke Christiaans4,5 | Ronald H. Lekanne Deprez4 | Hanne M. Boen6 | Emeline M. van Craenenbroeck6 | Bart L. Loeys7 | Yvonne M. Hoedemaekers5,8 | Carlo Marcelis8 | Marlies Kempers8 | Esther Brusse9 | Jaap I. van Waning10,11 | Annette F. Baas12 | Dennis Dooijes12 | Folkert W. Asselbergs13 | Daniela Q. C. M. Barge‐Schaapveld14 | Pieter Koopman15 | Arthur van den Wijngaard1 | Stephane R. B. Heymans2,16,17 | Ingrid P. C. Krapels1 | Han G. Brunner1,8,18 1Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands 2Department of Cardiology, Cardiovascular Research Institute (CARIM), Maastricht University Medical Center, Maastricht, The Netherlands 3Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands 4Department of Clinical Genetics, Amsterdam University Medical Center, Amsterdam, The Netherlands 5Department of Clinical Genetics, University Medical Centre Groningen, Groningen, The Netherlands 6Department of Cardiology, Antwerp University Hospital, University of Antwerp, Antwerp, Belgium 7Department of Medical Genetics, Antwerp University Hospital, University of Antwerp, Antwerp, Belgium -
Non-Coding Rnas As Cancer Hallmarks in Chronic Lymphocytic Leukemia
International Journal of Molecular Sciences Review Non-Coding RNAs as Cancer Hallmarks in Chronic Lymphocytic Leukemia Linda Fabris 1, Jaroslav Juracek 2 and George Calin 1,* 1 Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; [email protected] 2 Department of Experimental Therapeutics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; [email protected] * Correspondence: [email protected] Received: 24 July 2020; Accepted: 10 September 2020; Published: 14 September 2020 Abstract: The discovery of non-coding RNAs (ncRNAs) and their role in tumor onset and progression has revolutionized the way scientists and clinicians study cancers. This discovery opened new layers of complexity in understanding the fine-tuned regulation of cellular processes leading to cancer. NcRNAs represent a heterogeneous group of transcripts, ranging from a few base pairs to several kilobases, that are able to regulate gene networks and intracellular pathways by interacting with DNA, transcripts or proteins. Deregulation of ncRNAs impinge on several cellular responses and can play a major role in each single hallmark of cancer. This review will focus on the most important short and long non-coding RNAs in chronic lymphocytic leukemia (CLL), highlighting their implications as potential biomarkers and therapeutic targets as they relate to the well-established hallmarks of cancer. The key molecular events in the onset of CLL will be contextualized, taking into account the role of the “dark matter” of the genome. Keywords: chronic lymphocytic leukemia; lncRNA; miRNA; hallmarks 1. Introduction: Current Status of Chronic Lymphocytic Leukemia Research Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults in the Western world, representing more than 30% of all leukemia cases [1]. -
Supplemental Material
Supplemental Table B ARGs in alphabetical order Symbol Title 3 months 6 months 9 months 12 months 23 months ANOVA Direction Category 38597 septin 2 1557 ± 44 1555 ± 44 1579 ± 56 1655 ± 26 1691 ± 31 0.05219 up Intermediate 0610031j06rik kidney predominant protein NCU-G1 491 ± 6 504 ± 14 503 ± 11 527 ± 13 534 ± 12 0.04747 up Early Adult 1G5 vesicle-associated calmodulin-binding protein 662 ± 23 675 ± 17 629 ± 16 617 ± 20 583 ± 26 0.03129 down Intermediate A2m alpha-2-macroglobulin 262 ± 7 272 ± 8 244 ± 6 290 ± 7 353 ± 16 0.00000 up Midlife Aadat aminoadipate aminotransferase (synonym Kat2) 180 ± 5 201 ± 12 223 ± 7 244 ± 14 275 ± 7 0.00000 up Early Adult Abca2 ATP-binding cassette, sub-family A (ABC1), member 2 958 ± 28 1052 ± 58 1086 ± 36 1071 ± 44 1141 ± 41 0.05371 up Early Adult Abcb1a ATP-binding cassette, sub-family B (MDR/TAP), member 1A 136 ± 8 147 ± 6 147 ± 13 155 ± 9 185 ± 13 0.01272 up Midlife Acadl acetyl-Coenzyme A dehydrogenase, long-chain 423 ± 7 456 ± 11 478 ± 14 486 ± 13 512 ± 11 0.00003 up Early Adult Acadvl acyl-Coenzyme A dehydrogenase, very long chain 426 ± 14 414 ± 10 404 ± 13 411 ± 15 461 ± 10 0.01017 up Late Accn1 amiloride-sensitive cation channel 1, neuronal (degenerin) 242 ± 10 250 ± 9 237 ± 11 247 ± 14 212 ± 8 0.04972 down Late Actb actin, beta 12965 ± 310 13382 ± 170 13145 ± 273 13739 ± 303 14187 ± 269 0.01195 up Midlife Acvrinp1 activin receptor interacting protein 1 304 ± 18 285 ± 21 274 ± 13 297 ± 21 341 ± 14 0.03610 up Late Adk adenosine kinase 1828 ± 43 1920 ± 38 1922 ± 22 2048 ± 30 1949 ± 44 0.00797 up Early -
Human Periprostatic Adipose Tissue: Secretome from Patients With
CANCER GENOMICS & PROTEOMICS 16 : 29-58 (2019) doi:10.21873/cgp.20110 Human Periprostatic Adipose Tissue: Secretome from Patients With Prostate Cancer or Benign Prostate Hyperplasia PAULA ALEJANDRA SACCA 1, OSVALDO NÉSTOR MAZZA 2, CARLOS SCORTICATI 2, GONZALO VITAGLIANO 3, GABRIEL CASAS 4 and JUAN CARLOS CALVO 1,5 1Institute of Biology and Experimental Medicine (IBYME), CONICET, Buenos Aires, Argentina; 2Department of Urology, School of Medicine, University of Buenos Aires, Clínical Hospital “José de San Martín”, Buenos Aires, Argentina; 3Department of Urology, Deutsches Hospital, Buenos Aires, Argentina; 4Department of Pathology, Deutsches Hospital, Buenos Aires, Argentina; 5Department of Biological Chemistry, School of Exact and Natural Sciences, University of Buenos Aires, Buenos Aires, Argentina Abstract. Background/Aim: Periprostatic adipose tissue Prostate cancer (PCa) is the second most common cancer in (PPAT) directs tumour behaviour. Microenvironment secretome men worldwide. While most men have indolent disease, provides information related to its biology. This study was which can be treated properly, the problem consists in performed to identify secreted proteins by PPAT, from both reliably distinguishing between indolent and aggressive prostate cancer and benign prostate hyperplasia (BPH) disease. Evidence shows that the microenvironment affects patients. Patients and Methods: Liquid chromatography-mass tumour behavior. spectrometry-based proteomic analysis was performed in Adipose tissue microenvironment is now known to direct PPAT-conditioned media (CM) from patients with prostate tumour growth, invasion and metastases (1, 2). Adipose cancer (CMs-T) (stage T3: CM-T3, stage T2: CM-T2) or tissue is adjacent to the prostate gland and the site of benign disease (CM-BPH). Results: The highest number and invasion of PCa. -
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. -
Proteins That Mediate Protein Aggregation and Cytotoxicity Distinguish Alzheimer'S Hippocampus from Normal Controls
Aging Cell (2016) pp1–16 Doi: 10.1111/acel.12501 Proteins that mediate protein aggregation and cytotoxicity distinguish Alzheimer’s hippocampus from normal controls Srinivas Ayyadevara,1,2 Meenakshisundaram types of aggregation, and/or aggregate-mediated cross-talk Balasubramaniam,2,3 Paul A. Parcon,2 Steven W. Barger,1,2 between tau and Ab. Knowledge of protein components that W. Sue T. Griffin,1,2 Ramani Alla,1,2 Alan J. Tackett,4 promote protein accrual in diverse aggregate types implicates Samuel G. Mackintosh,4 Emanuel Petricoin,5 Weidong Zhou5 common mechanisms and identifies novel targets for drug and Robert J. Shmookler Reis1,2,4 intervention. Key words: Abeta(1-42); acetylation (protein); aggregation 1McClellan Veterans Medical Center, Central Arkansas Veterans Healthcare Service, Little Rock, AR 72205, USA (protein); Alzheimer (Disease); beta amyloid; C. elegans; 2Department of Geriatrics, University of Arkansas for Medical Sciences, Little microtubule-associated protein tau; neurodegeneration; Rock, AR 72205, USA neurotoxicity; oxidation (protein); phosphorylation (protein); 3BioInformatics Program, University of Arkansas for Medical Sciences and University of Arkansas at Little Rock, Little Rock, AR 72205, USA proteomics. 4Department of Biochemistry & Molecular Biology, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA 5 Center for Applied Proteomics and Molecular Medicine, George Mason Introduction University, Manassas, VA 20110, USA Summary Protein aggregation has long been recognized as a common feature of most or all age-dependent neurodegenerative diseases, and yet very little Neurodegenerative diseases are distinguished by characteristic is known about which features of aggregating proteins contribute to protein aggregates initiated by disease-specific ‘seed’ proteins; their accrual or their neurotoxicity. -
Predicting Coupling Probabilities of G-Protein Coupled Receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J
Published online 30 May 2019 Nucleic Acids Research, 2019, Vol. 47, Web Server issue W395–W401 doi: 10.1093/nar/gkz392 PRECOG: PREdicting COupling probabilities of G-protein coupled receptors Gurdeep Singh1,2,†, Asuka Inoue3,*,†, J. Silvio Gutkind4, Robert B. Russell1,2,* and Francesco Raimondi1,2,* 1CellNetworks, Bioquant, Heidelberg University, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany, 2Biochemie Zentrum Heidelberg (BZH), Heidelberg University, Im Neuenheimer Feld 328, 69120 Heidelberg, Germany, 3Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai, Miyagi 980-8578, Japan and 4Department of Pharmacology and Moores Cancer Center, University of California, San Diego, La Jolla, CA 92093, USA Received February 10, 2019; Revised April 13, 2019; Editorial Decision April 24, 2019; Accepted May 01, 2019 ABSTRACT great use in tinkering with signalling pathways in living sys- tems (5). G-protein coupled receptors (GPCRs) control multi- Ligand binding to GPCRs induces conformational ple physiological states by transducing a multitude changes that lead to binding and activation of G-proteins of extracellular stimuli into the cell via coupling to situated on the inner cell membrane. Most of mammalian intra-cellular heterotrimeric G-proteins. Deciphering GPCRs couple with more than one G-protein giving each which G-proteins couple to each of the hundreds receptor a distinct coupling profile (6) and thus specific of GPCRs present in a typical eukaryotic organism downstream cellular responses. Determining these coupling is therefore critical to understand signalling. Here, profiles is critical to understand GPCR biology and phar- we present PRECOG (precog.russelllab.org): a web- macology. Despite decades of research and hundreds of ob- server for predicting GPCR coupling, which allows served interactions, coupling information is still missing for users to: (i) predict coupling probabilities for GPCRs many receptors and sequence determinants of coupling- specificity are still largely unknown. -
CXCR4 Pathway Retards Muscle Atrophy During Cancer Cachexia
Oncogene (2016) 35, 6212–6222 © 2016 Macmillan Publishers Limited, part of Springer Nature. All rights reserved 0950-9232/16 www.nature.com/onc ORIGINAL ARTICLE Activation of the SDF1/CXCR4 pathway retards muscle atrophy during cancer cachexia GB Martinelli1, D Olivari1, AD Re Cecconi1, L Talamini1, L Ottoboni2, SH Lecker3, C Stretch4, VE Baracos4, OF Bathe5, A Resovi6, R Giavazzi1, L Cervo7 and R Piccirillo1 Cancer cachexia is a life-threatening syndrome that affects most patients with advanced cancers and causes severe body weight loss, with rapid depletion of skeletal muscle. No treatment is available. We analyzed microarray data sets to identify a subset of genes whose expression is specifically altered in cachectic muscles of Yoshida hepatoma-bearing rodents but not in those with diabetes, disuse, uremia or fasting. Ingenuity Pathways Analysis indicated that three genes belonging to the C-X-C motif chemokine receptor 4 (CXCR4) pathway were downregulated only in muscles atrophying because of cancer: stromal cell-derived factor 1 (SDF1), adenylate cyclase 7 (ADCY7), and p21 protein-activated kinase 1 (PAK1). Notably, we found that, in the Rectus Abdominis muscle of cancer patients, the expression of SDF1 and CXCR4 was inversely correlated with that of two ubiquitin ligases induced in muscle wasting, atrogin-1 and MuRF1, suggesting a possible clinical relevance of this pathway. The expression of all main SDF1 isoforms (α, β, γ) also declined in Tibialis Anterior muscle from cachectic mice bearing murine colon adenocarcinoma or human renal cancer and drugs with anticachexia properties restored their expression. Overexpressing genes of this pathway (that is, SDF1 or CXCR4) in cachectic muscles increased the fiber area by 20%, protecting them from wasting. -
Product Description SALSA® MS-MLPA® Probemix ME031-C1 GNAS to Be Used with the MS-MLPA General Protocol
Product description version C1-01; Issued 19 March 2021 Product Description SALSA® MS-MLPA® Probemix ME031-C1 GNAS To be used with the MS-MLPA General Protocol. Version C1 As compared to version B2, probemix completely revised, details are shown in complete product history see page 11. Catalogue numbers: ME031-025R: SALSA MS-MLPA Probemix ME031 GNAS, 25 reactions. ME031-050R: SALSA MS-MLPA Probemix ME031 GNAS, 50 reactions. ME031-100R: SALSA MS-MLPA Probemix ME031 GNAS, 100 reactions. To be used in combination with a SALSA MLPA reagent kit, SALSA HhaI (SMR50) and Coffalyser.Net data analysis software. MLPA reagent kits are either provided with FAM or Cy5.0 dye-labelled PCR primer, suitable for Applied Biosystems and Beckman/SCIEX capillary sequencers, respectively (see www.mrcholland.com). Certificate of Analysis Information regarding storage conditions, quality tests, and a sample electropherogram from the current sales lot is available at www.mrcholland.com. Precautions and warnings For professional use only. Always consult the most recent product description AND the MS-MLPA General Protocol before use: www.mrcholland.com. It is the responsibility of the user to be aware of the latest scientific knowledge of the application before drawing any conclusions from findings generated with this product. This SALSA MS-MLPA probemix is intended for experienced MLPA users only! The exact link between the GNAS complex locus genotype and phenotype is still being investigated. Use of this ME031 GNAS probemix will not always provide you with clear-cut answers and interpretation of results can therefore be complicated. MRC Holland can only provide limited support with interpretation of results obtained with this product, and recommends thoroughly screening any available literature. -
Functional Characterisation of Human Synaptic Genes Expressed in the Drosophila Brain Lysimachos Zografos1,2, Joanne Tang1, Franziska Hesse3, Erich E
© 2016. Published by The Company of Biologists Ltd | Biology Open (2016) 5, 662-667 doi:10.1242/bio.016261 METHODS & TECHNIQUES Functional characterisation of human synaptic genes expressed in the Drosophila brain Lysimachos Zografos1,2, Joanne Tang1, Franziska Hesse3, Erich E. Wanker3, Ka Wan Li4, August B. Smit4, R. Wayne Davies1,5 and J. Douglas Armstrong1,5,* ABSTRACT systems biology approaches are likely to be the best route to unlock a Drosophila melanogaster is an established and versatile model new generation of neuroscience research and CNS drug organism. Here we describe and make available a collection of development that society so urgently demands (Catalá-López transgenic Drosophila strains expressing human synaptic genes. The et al., 2013). Yet these modelling type approaches also need fast, collection can be used to study and characterise human synaptic tractable in vivo models for validation. genes and their interactions and as controls for mutant studies. It was More than 100 years after the discovery of the white gene in generated in a way that allows the easy addition of new strains, as well Drosophila melanogaster, the common fruit fly remains a key tool as their combination. In order to highlight the potential value of the for the study of neuroscience and neurobiology. The fruit fly collection for the characterisation of human synaptic genes we also genome is well annotated and there is a vast genetic manipulation use two assays, investigating any gain-of-function motor and/or toolkit available. This allows interventions such as high throughput cognitive phenotypes in the strains in this collection. Using these cloning (Bischof et al., 2013; Wang et al., 2012) and the precise assays we show that among the strains made there are both types of insertion of transgenes in the genome (Groth et al., 2004; Venken gain-of-function phenotypes investigated.