Nuclear Organization and the Epigenetic Landscape of the Mus Musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected]

Total Page:16

File Type:pdf, Size:1020Kb

Nuclear Organization and the Epigenetic Landscape of the Mus Musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, Alicia.Liu@Uconn.Edu University of Connecticut OpenCommons@UConn Doctoral Dissertations University of Connecticut Graduate School 8-9-2019 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia Liu University of Connecticut - Storrs, [email protected] Follow this and additional works at: https://opencommons.uconn.edu/dissertations Recommended Citation Liu, Alicia, "Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome" (2019). Doctoral Dissertations. 2273. https://opencommons.uconn.edu/dissertations/2273 Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia J. Liu, Ph.D. University of Connecticut, 2019 ABSTRACT X-linked imprinted genes have been hypothesized to contribute parent-of-origin influences on social cognition. A cluster of imprinted genes Xlr3b, Xlr4b, and Xlr4c, implicated in cognitive defects, are maternally expressed and paternally silent in the murine brain. These genes defy classic mechanisms of autosomal imprinting, suggesting a novel method of imprinted gene regulation. Using Xlr3b and Xlr4c as bait, this study uses 4C-Seq on neonatal whole brain of a 39,XO mouse model, to provide the first in-depth analysis of chromatin dynamics surrounding an imprinted locus on the X-chromosome. Significant differences in long-range contacts exist be- tween XM and XP monosomic samples. In addition, XM interaction profiles contact a greater number of genes linked to cognitive impairment, abnormality of the nervous system, and abnormality of higher mental function. This is not a pattern that is unique to the imprinted Xlr3/4 locus. Additional Alicia J. Liu - University of Connecticut - 2019 4C-Seq experiments show that other genes on the X-chromosome, implicated in intellectual disability and/or ASD, also produce more maternal contacts to other X-linked genes linked to cognitive impairment. The observation that there are dif- ferences between the maternal and paternal X interactomes is bolstered by potential variation in Atrx binding and H3K27me3 enrichment between XM and XP, sug- gesting that there may be broad-scale differences of the X-chromosome, related to parent-of-origin effects. Taken together, these results provide intriguing insight into the maternal X susceptibility to cognitive and social impairment. Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Alicia J. Liu Bachelor of Science, University of Delaware, 2012 A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Connecticut 2019 Copyright by Alicia J. Liu 2019 i APPROVAL PAGE Doctor of Philosophy Dissertation Nuclear Organization and the Epigenetic Landscape of the Mus musculus X-Chromosome Presented by Alicia J. Liu, B.S. Major Advisor Michael O’Neill Associate Advisor Rachel O’Neill Associate Advisor John Malone University of Connecticut 2019 ii To Fat Stanley, protector of the pumpkin patch. iii ACKNOWLEDGEMENTS I wish to express my deepest gratitude to the people in my life whose encourage- ment and support made this dissertation possible. First and foremost, the biggest thanks go to Mike. Thank you for being my advi- sor. Thank you for inspiring me and motivating me to meet every challenge, while also giving me the independence to grow and mature into the scientist I am today. The skills I learned in your lab I will carry with me the rest of my life. Besides my advisor, I extend thanks to the rest of my committee members for their years of support and invaluable advice. Rachel and John, your insights have been an incredible resource to me over the course of this dissertation. Leighton and Bibi, your course work and expertise provided the foundation upon which a lot of this work was built. What I have learned from my committee has been a tremendous help in designing and analyzing experiments, and for that I am incredibly grateful. I would also like to thank my lab mates, both past and present, for their contin- ued support, and for making the M. O’Neill lab a wonderful, fun, and productive environment. Natali, for always being there as a great friend and supportive brain to lean on. Rob, who answered my endless questions and was always willing to lend a helping hand. And to Glenn, Matt, Katelyn, and Tyler, thank you. Special thanks go to Dylan. You are my motivation and my inspiration. Your unwavering faith in me made this possible. Last but not least, I would like to thank my friends and family for their constant encouragement, love, and support throughout my long graduate career. Thank you. iv TABLE OF CONTENTS Introduction : Setting the Problem :::::::::::::::::::::::::::::::::::::::: 1 0.1. Overview . .1 0.2. Genomic Imprinting . .3 0.3. Eutherian X-Chromosome Dosage Compensation . .5 0.4. Turner Syndrome . .6 0.5. Autism Spectrum Disorder . .8 0.6. X-linked Genomic Imprinting . 10 0.7. Mechanisms of Epigenetic and Imprinting Regulation . 12 0.7.1. Differential DNA Methylation . 13 0.7.2. Allele-Specific Histone Modification . 14 0.7.3. Interactome Analyses of Imprinted Domains . 16 Ch. 1 : Nuclear Organization of the Imprinted Xlr3/4 Locus ::::::::::::::::: 18 1.1. Abstract . 18 1.2. Background . 19 1.3. Results . 24 1.3.1. Generating a library of genome-wide chromatin interactions . 24 1.3.2. Long-range interactions at the imprinted Xlr3/4 locus . 25 1.3.3. 4C domains reside in open chromosomal compartments . 30 1.3.4. Short-range comprehensive analysis of looping interactions . 33 1.3.5. 4C domains enriched with genes linked to cognitive impairment . 40 1.4. Discussion . 45 Ch. 2 : Epigenomic Profiling of the Maternal and Paternal X-Chromosomes :: 48 2.1. Abstract . 48 2.2. Background . 49 2.3. Results . 53 2.3.1. Interaction profiles of the maternal and paternal X-chromosomes . 53 2.3.2. XM 4C domains are enriched with genes involved in cognitive function . 55 2.3.3. X-chromosome profiling of H3K27me3 and Atrx . 58 2.4. Discussion . 68 Ch. 3 : Regulation of Xlr3b Gene Expression ::::::::::::::::::::::::::::::: 73 3.1. Background . 73 3.2. Results . 78 3.3. Discussion . 83 Ch. 4 : Synthesis and Future Directions ::::::::::::::::::::::::::::::::::: 86 v Ch. 5 : Materials and Methods :::::::::::::::::::::::::::::::::::::::::::: 93 5.1. Animal Breeding and Tissue Collection . 93 5.2. Xlr3b Expression Analysis . 93 5.3. Chromosome Conformation Capture (3C) . 94 5.3.1. Mouse Neonatal Brain Tissue . 94 5.3.2. Mouse Fibroblast Cultured Cells . 96 5.4. 3C-Carbon Copy (5C-Seq) . 97 5.4.1. 3C Control Library Generation . 97 5.4.2. 5C Primers and Library Generation . 97 5.4.3. Illumina MiSeq Sequencing . 98 5.4.4. Data Analysis . 98 5.5. Circular 3C (4C-Seq) . 99 5.5.1. 4C Primers and Library Generation . 99 5.5.2. Illumina NextSeq500 Sequencing . 100 5.5.3. Data Analysis . 101 5.6. Chromatin Immunoprecipitation (ChIP-Seq) . 102 5.6.1. ChIP Library Generation . 102 5.6.2. Illumina NextSeq500 Sequencing . 103 5.6.3. Data Analysis . 103 5.7. Assay for Transposase-Accessible Chromatin (ATAC-Seq) . 103 App. A : :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 104 A.1. Primers . 104 A.2. BACs............................................................... 118 A.3. Antibodies . 118 App. B : :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 119 B.1. Sequencing Metrics . 119 Bibliography :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 125 vi LIST OF FIGURES 0.4.1 Cognitive defects in individuals with Turner syndrome. .7 0.6.2 Genomic imprinting of Xlr3b, Xlr4b, and Xlr4c......................... 11 0.6.3 Schematic representation of the Xlr3/4/5 locus. 12 0.7.4 Increased Xlr3b expression in 5-aza-2-dC treated cell lines. 15 1.2.1 Overview of 3C-derived methods. 21 1.3.1 Overview of 4C-Seq bait region at the imprinted Xlr3/4 locus. 25 1.3.2 Distribution of 4C-Seq reads. 26 1.3.3 Distribution of 4C interactions. 27 1.3.4 Significant 4C domains in cis and in trans.............................. 28 1.3.5 Long-range cis interactions of Xlr3b and Xlr4c.......................... 29 1.3.6 DNA replication timing of 4C domains. 31 1.3.7 Enrichment of active chromatin signatures around 4C domains. 32 1.3.8 Repetitive elements within 4C domains. 34 1.3.9 Near-bait interactions of Xlr3b and Xlr4c.............................. 35 1.3.10 Near-bait interactions show parent-specific differences within a TAD. 36 1.3.11 Overview of 5C-Seq primer design at the imprinted Xlr3/4 locus. 37 1.3.12 5C interaction profile of Xlr3b........................................ 38 1.3.13 4C interacting regions display characteristics of regulatory elements. 39 1.3.14 Distribution of region-gene associations within 4C domains. 41 1.3.15 Functional annotation of genes within Xlr4c 4C domains. 42 1.3.16 Functional annotation of genes within Xlr3b 4C domains. 44 2.3.1 Significant 4C domains of six viewpoints across the X-chromosome. 54 2.3.2 Number of associated genes per 4C domain. ..
Recommended publications
  • Downloaded from Bioscientifica.Com at 09/27/2021 05:40:52PM Via Free Access 328 I J BUJALSKA and Others
    327 Expression profiling of 11b-hydroxysteroid dehydrogenase type-1 and glucocorticoid-target genes in subcutaneous and omental human preadipocytes I J Bujalska1, M Quinkler1,3, J W Tomlinson1, C T Montague2, D M Smith2 and P M Stewart1 1Division of Medical Sciences, The Medical School, Institute of Biomedical Research, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK 2Diabetes Drug Discovery, AstraZeneca, Alderley Park, Macclesfield, Cheshire SK10 4TG, UK 3Clinical Endocrinology, Campus Mitte, Charite´ Universita¨tsmedizin Berlin, Berlin, Germany (Requests for offprints should be addressed to P M Stewart; Email: [email protected]) Abstract Obesity is associated with increased morbidity and mortality from cardiovascular disease, diabetes and cancer. Although obesity is a multi-factorial heterogeneous condition, fat accumulation in visceral depots is most highly associated with these risks. Pathological glucocorticoid excess (i.e. in Cushing’s syndrome) is a recognised, reversible cause of visceral fat accumulation. The aim of this study was to identify depot-specific glucocorticoid-target genes in adipocyte precursor cells (preadipocytes) using Affymetrix microarray technique. Confluent preadipocytes from subcutaneous (SC) and omental (OM) adipose tissue collected from five female patients were treated for 24 h with 100 nM cortisol (F), RNA was pooled and hybridised to the Affymetrix U133 microarray set. We identified 72 upregulated and 30 downregulated genes by F in SC cells. In OM preadipocytes, 56 genes were increased and 19 were decreased. Among the most interesting were transcription factors, markers of adipocyte differentiation and glucose metabolism, cell adhesion and growth arrest protein factors involved in G-coupled and Wnt signalling. The Affymetrix data have been confirmed by quantitative real- time PCR for ten specific genes, including HSD11B1, GR, C/EBPa, C/EBPb, IL-6, FABP4, APOD, IRS2, AGTR1 and GHR.
    [Show full text]
  • PARSANA-DISSERTATION-2020.Pdf
    DECIPHERING TRANSCRIPTIONAL PATTERNS OF GENE REGULATION: A COMPUTATIONAL APPROACH by Princy Parsana A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy Baltimore, Maryland July, 2020 © 2020 Princy Parsana All rights reserved Abstract With rapid advancements in sequencing technology, we now have the ability to sequence the entire human genome, and to quantify expression of tens of thousands of genes from hundreds of individuals. This provides an extraordinary opportunity to learn phenotype relevant genomic patterns that can improve our understanding of molecular and cellular processes underlying a trait. The high dimensional nature of genomic data presents a range of computational and statistical challenges. This dissertation presents a compilation of projects that were driven by the motivation to efficiently capture gene regulatory patterns in the human transcriptome, while addressing statistical and computational challenges that accompany this data. We attempt to address two major difficulties in this domain: a) artifacts and noise in transcriptomic data, andb) limited statistical power. First, we present our work on investigating the effect of artifactual variation in gene expression data and its impact on trans-eQTL discovery. Here we performed an in-depth analysis of diverse pre-recorded covariates and latent confounders to understand their contribution to heterogeneity in gene expression measurements. Next, we discovered 673 trans-eQTLs across 16 human tissues using v6 data from the Genotype Tissue Expression (GTEx) project. Finally, we characterized two trait-associated trans-eQTLs; one in Skeletal Muscle and another in Thyroid. Second, we present a principal component based residualization method to correct gene expression measurements prior to reconstruction of co-expression networks.
    [Show full text]
  • De Novo Transcriptome Analysis of White Teak (Gmelina Arborea Roxb
    Yaya Lancheros et al. BMC Genomics (2021) 22:494 https://doi.org/10.1186/s12864-021-07777-x RESEARCH ARTICLE Open Access De novo transcriptome analysis of white teak (Gmelina arborea Roxb) wood reveals critical genes involved in xylem development and secondary metabolism Mary Luz Yaya Lancheros1, Krishan Mohan Rai2,3, Vimal Kumar Balasubramanian2,4, Lavanya Dampanaboina2, Venugopal Mendu2 and Wilson Terán1* Abstract Background: Gmelina arborea Roxb is a fast-growing tree species of commercial importance for tropical countries due to multiple industrial uses of its wood. Wood is primarily composed of thick secondary cell walls of xylem cells which imparts the strength to the wood. Identification of the genes involved in the secondary cell wall biosynthesis as well as their cognate regulators is crucial to understand how the production of wood occurs and serves as a starting point for developing breeding strategies to produce varieties with improved wood quality, better paper pulping or new potential uses such as biofuel production. In order to gain knowledge on the molecular mechanisms and gene regulation related with wood development in white teak, a de novo sequencing and transcriptome assembly approach was used employing secondary cell wall synthesizing cells from young white teak trees. Results: For generation of transcriptome, RNA-seq reads were assembled into 110,992 transcripts and 49,364 genes were functionally annotated using plant databases; 5071 GO terms and 25,460 SSR markers were identified within xylem transcripts and 10,256 unigenes were assigned to KEGG database in 130 pathways. Among transcription factor families, C2H2, C3H, bLHLH and MYB were the most represented in xylem.
    [Show full text]
  • IMGT-ONTOLOGY and IMGT Databases, Tools and Web
    Molecular Immunology 40 (2004) 647–660 Review IMGT-ONTOLOGY and IMGT databases, tools and Web resources for immunogenetics and immunoinformatics Marie-Paule Lefranc a,b,∗ a Laboratoire d’ImmunoGénétique Moléculaire, LIGM, Institut de Génétique Humaine IGH, Université Montpellier II, UPR CNRS 1142, 141 rue de la Cardonille, 34396 Montpellier Cedex 5, France b Institut Universitaire de France, France Received 18 June 2003; received in revised form 2 September 2003; accepted 16 September 2003 Abstract The international ImMunoGeneTics information system® (IMGT; http://imgt.cines.fr), is a high quality integrated information system specialized in immunoglobulins (IG), T cell receptors (TR), major histocompatibility complex (MHC), and related proteins of the immune system (RPI) of human and other vertebrates, created in 1989, by the Laboratoire d’ImmunoGénétique Moléculaire (LIGM; Université Montpellier II and CNRS) at Montpellier, France. IMGT provides a common access to standardized data which include nucleotide and protein sequences, oligonucleotide primers, gene maps, genetic polymorphisms, specificities, 2D and 3D structures. IMGT consists of several sequence databases (IMGT/LIGM-DB, IMGT/MHC-DB, IMGT/PRIMER-DB), one genome database (IMGT/GENE-DB) and one 3D structure database (IMGT/3Dstructure-DB), interactive tools for sequence analysis (IMGT/V-QUEST, IMGT/JunctionAnalysis, IMGT/PhyloGene, IMGT/Allele-Align), for genome analysis (IMGT/GeneSearch, IMGT/GeneView, IMGT/LocusView) and for 3D struc- ture analysis (IMGT/StructuralQuery), and
    [Show full text]
  • Analysis of Gene Expression Data for Gene Ontology
    ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION A Thesis Presented to The Graduate Faculty of The University of Akron In Partial Fulfillment of the Requirements for the Degree Master of Science Robert Daniel Macholan May 2011 ANALYSIS OF GENE EXPRESSION DATA FOR GENE ONTOLOGY BASED PROTEIN FUNCTION PREDICTION Robert Daniel Macholan Thesis Approved: Accepted: _______________________________ _______________________________ Advisor Department Chair Dr. Zhong-Hui Duan Dr. Chien-Chung Chan _______________________________ _______________________________ Committee Member Dean of the College Dr. Chien-Chung Chan Dr. Chand K. Midha _______________________________ _______________________________ Committee Member Dean of the Graduate School Dr. Yingcai Xiao Dr. George R. Newkome _______________________________ Date ii ABSTRACT A tremendous increase in genomic data has encouraged biologists to turn to bioinformatics in order to assist in its interpretation and processing. One of the present challenges that need to be overcome in order to understand this data more completely is the development of a reliable method to accurately predict the function of a protein from its genomic information. This study focuses on developing an effective algorithm for protein function prediction. The algorithm is based on proteins that have similar expression patterns. The similarity of the expression data is determined using a novel measure, the slope matrix. The slope matrix introduces a normalized method for the comparison of expression levels throughout a proteome. The algorithm is tested using real microarray gene expression data. Their functions are characterized using gene ontology annotations. The results of the case study indicate the protein function prediction algorithm developed is comparable to the prediction algorithms that are based on the annotations of homologous proteins.
    [Show full text]
  • Transcriptional Regulation of RKIP in Prostate Cancer Progression
    Health Science Campus FINAL APPROVAL OF DISSERTATION Doctor of Philosophy in Biomedical Sciences Transcriptional Regulation of RKIP in Prostate Cancer Progression Submitted by: Sandra Marie Beach In partial fulfillment of the requirements for the degree of Doctor of Philosophy in Biomedical Sciences Examination Committee Major Advisor: Kam Yeung, Ph.D. Academic William Maltese, Ph.D. Advisory Committee: Sonia Najjar, Ph.D. Han-Fei Ding, M.D., Ph.D. Manohar Ratnam, Ph.D. Senior Associate Dean College of Graduate Studies Michael S. Bisesi, Ph.D. Date of Defense: May 16, 2007 Transcriptional Regulation of RKIP in Prostate Cancer Progression Sandra Beach University of Toledo ACKNOWLDEGMENTS I thank my major advisor, Dr. Kam Yeung, for the opportunity to pursue my degree in his laboratory. I am also indebted to my advisory committee members past and present, Drs. Sonia Najjar, Han-Fei Ding, Manohar Ratnam, James Trempe, and Douglas Pittman for generously and judiciously guiding my studies and sharing reagents and equipment. I owe extended thanks to Dr. William Maltese as a committee member and chairman of my department for supporting my degree progress. The entire Department of Biochemistry and Cancer Biology has been most kind and helpful to me. Drs. Roy Collaco and Hong-Juan Cui have shared their excellent technical and practical advice with me throughout my studies. I thank members of the Yeung laboratory, Dr. Sungdae Park, Hui Hui Tang, Miranda Yeung for their support and collegiality. The data mining studies herein would not have been possible without the helpful advice of Dr. Robert Trumbly. I am also grateful for the exceptional assistance and shared microarray data of Dr.
    [Show full text]
  • Protein Interaction Network of Alternatively Spliced Isoforms from Brain Links Genetic Risk Factors for Autism
    ARTICLE Received 24 Aug 2013 | Accepted 14 Mar 2014 | Published 11 Apr 2014 DOI: 10.1038/ncomms4650 OPEN Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism Roser Corominas1,*, Xinping Yang2,3,*, Guan Ning Lin1,*, Shuli Kang1,*, Yun Shen2,3, Lila Ghamsari2,3,w, Martin Broly2,3, Maria Rodriguez2,3, Stanley Tam2,3, Shelly A. Trigg2,3,w, Changyu Fan2,3, Song Yi2,3, Murat Tasan4, Irma Lemmens5, Xingyan Kuang6, Nan Zhao6, Dheeraj Malhotra7, Jacob J. Michaelson7,w, Vladimir Vacic8, Michael A. Calderwood2,3, Frederick P. Roth2,3,4, Jan Tavernier5, Steve Horvath9, Kourosh Salehi-Ashtiani2,3,w, Dmitry Korkin6, Jonathan Sebat7, David E. Hill2,3, Tong Hao2,3, Marc Vidal2,3 & Lilia M. Iakoucheva1 Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.
    [Show full text]
  • Linked Mental Retardation Detected by Array CGH
    JMG Online First, published on September 16, 2005 as 10.1136/jmg.2005.036178 J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from Chromosomal copy number changes in patients with non-syndromic X- linked mental retardation detected by array CGH D Lugtenberg1, A P M de Brouwer1, T Kleefstra1, A R Oudakker1, S G M Frints2, C T R M Schrander- Stumpel2, J P Fryns3, L R Jensen4, J Chelly5, C Moraine6, G Turner7, J A Veltman1, B C J Hamel1, B B A de Vries1, H van Bokhoven1, H G Yntema1 1Department of Human Genetics, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands; 2Department of Clinical Genetics, University Hospital Maastricht, Maastricht, The Netherlands; 3Center for Human Genetics, University of Leuven, Leuven, Belgium; 4Max Planck Institute for Molecular Genetics, Berlin, Germany; 5INSERM 129-ICGM, Faculté de Médecine Cochin, Paris, France; 6Service de Génétique et INSERM U316, Hôpital Bretonneau, Tours, France; 7 GOLD Program, Hunter Genetics, University of Newcastle, Callaghan, New South Wales 2308, Australia http://jmg.bmj.com/ Corresponding author: on October 2, 2021 by guest. Protected copyright. Helger G. Yntema, PhD Department of Human Genetics Radboud University Nijmegen Medical Centre P.O. Box 9101 6500 HB Nijmegen The Netherlands E-mail: [email protected] tel: +31-24-3613799 fax: +31-24-3616658 1 Copyright Article author (or their employer) 2005. Produced by BMJ Publishing Group Ltd under licence. J Med Genet: first published as 10.1136/jmg.2005.036178 on 16 September 2005. Downloaded from ABSTRACT Introduction: Several studies have shown that array based comparative genomic hybridization (array CGH) is a powerful tool for the detection of copy number changes in the genome of individuals with a congenital disorder.
    [Show full text]
  • Gene Knockdown of CENPA Reduces Sphere Forming Ability and Stemness of Glioblastoma Initiating Cells
    Neuroepigenetics 7 (2016) 6–18 Contents lists available at ScienceDirect Neuroepigenetics journal homepage: www.elsevier.com/locate/nepig Gene knockdown of CENPA reduces sphere forming ability and stemness of glioblastoma initiating cells Jinan Behnan a,1, Zanina Grieg b,c,1, Mrinal Joel b,c, Ingunn Ramsness c, Biljana Stangeland a,b,⁎ a Department of Molecular Medicine, Institute of Basic Medical Sciences, The Medical Faculty, University of Oslo, Oslo, Norway b Norwegian Center for Stem Cell Research, Department of Immunology and Transfusion Medicine, Oslo University Hospital, Oslo, Norway c Vilhelm Magnus Laboratory for Neurosurgical Research, Institute for Surgical Research and Department of Neurosurgery, Oslo University Hospital, Oslo, Norway article info abstract Article history: CENPA is a centromere-associated variant of histone H3 implicated in numerous malignancies. However, the Received 20 May 2016 role of this protein in glioblastoma (GBM) has not been demonstrated. GBM is one of the most aggressive Received in revised form 23 July 2016 human cancers. GBM initiating cells (GICs), contained within these tumors are deemed to convey Accepted 2 August 2016 characteristics such as invasiveness and resistance to therapy. Therefore, there is a strong rationale for targeting these cells. We investigated the expression of CENPA and other centromeric proteins (CENPs) in Keywords: fi CENPA GICs, GBM and variety of other cell types and tissues. Bioinformatics analysis identi ed the gene signature: fi Centromeric proteins high_CENP(AEFNM)/low_CENP(BCTQ) whose expression correlated with signi cantly worse GBM patient Glioblastoma survival. GBM Knockdown of CENPA reduced sphere forming ability, proliferation and cell viability of GICs. We also Brain tumor detected significant reduction in the expression of stemness marker SOX2 and the proliferation marker Glioblastoma initiating cells and therapeutic Ki67.
    [Show full text]
  • 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.
    [Show full text]
  • The Inactive X Chromosome Is Epigenetically Unstable and Transcriptionally Labile in Breast Cancer
    Supplemental Information The inactive X chromosome is epigenetically unstable and transcriptionally labile in breast cancer Ronan Chaligné1,2,3,8, Tatiana Popova1,4, Marco-Antonio Mendoza-Parra5, Mohamed-Ashick M. Saleem5 , David Gentien1,6, Kristen Ban1,2,3,8, Tristan Piolot1,7, Olivier Leroy1,7, Odette Mariani6, Hinrich Gronemeyer*5, Anne Vincent-Salomon*1,4,6,8, Marc-Henri Stern*1,4,6 and Edith Heard*1,2,3,8 Extended Experimental Procedures Cell Culture Human Mammary Epithelial Cells (HMEC, Invitrogen) were grown in serum-free medium (HuMEC, Invitrogen). WI- 38, ZR-75-1, SK-BR-3 and MDA-MB-436 cells were grown in Dulbecco’s modified Eagle’s medium (DMEM; Invitrogen) containing 10% fetal bovine serum (FBS). DNA Methylation analysis. We bisulfite-treated 2 µg of genomic DNA using Epitect bisulfite kit (Qiagen). Bisulfite converted DNA was amplified with bisulfite primers listed in Table S3. All primers incorporated a T7 promoter tag, and PCR conditions are available upon request. We analyzed PCR products by MALDI-TOF mass spectrometry after in vitro transcription and specific cleavage (EpiTYPER by Sequenom®). For each amplicon, we analyzed two independent DNA samples and several CG sites in the CpG Island. Design of primers and selection of best promoter region to assess (approx. 500 bp) were done by a combination of UCSC Genome Browser (http://genome.ucsc.edu) and MethPrimer (http://www.urogene.org). All the primers used are listed (Table S3). NB: MAGEC2 CpG analysis have been done with a combination of two CpG island identified in the gene core. Analysis of RNA allelic expression profiles (based on Human SNP Array 6.0) DNA and RNA hybridizations were normalized by Genotyping console.
    [Show full text]
  • Downloaded from [266]
    Patterns of DNA methylation on the human X chromosome and use in analyzing X-chromosome inactivation by Allison Marie Cotton B.Sc., The University of Guelph, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Medical Genetics) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) January 2012 © Allison Marie Cotton, 2012 Abstract The process of X-chromosome inactivation achieves dosage compensation between mammalian males and females. In females one X chromosome is transcriptionally silenced through a variety of epigenetic modifications including DNA methylation. Most X-linked genes are subject to X-chromosome inactivation and only expressed from the active X chromosome. On the inactive X chromosome, the CpG island promoters of genes subject to X-chromosome inactivation are methylated in their promoter regions, while genes which escape from X- chromosome inactivation have unmethylated CpG island promoters on both the active and inactive X chromosomes. The first objective of this thesis was to determine if the DNA methylation of CpG island promoters could be used to accurately predict X chromosome inactivation status. The second objective was to use DNA methylation to predict X-chromosome inactivation status in a variety of tissues. A comparison of blood, muscle, kidney and neural tissues revealed tissue-specific X-chromosome inactivation, in which 12% of genes escaped from X-chromosome inactivation in some, but not all, tissues. X-linked DNA methylation analysis of placental tissues predicted four times higher escape from X-chromosome inactivation than in any other tissue. Despite the hypomethylation of repetitive elements on both the X chromosome and the autosomes, no changes were detected in the frequency or intensity of placental Cot-1 holes.
    [Show full text]