Title 1 Transcriptomic Analysis of Ribosome Biogenesis and Pre-Rrna
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Different Genetic Mechanisms Mediate Spontaneous Versus UVR-Induced
RESEARCH ARTICLE Different genetic mechanisms mediate spontaneous versus UVR-induced malignant melanoma Blake Ferguson1, Herlina Y Handoko1, Pamela Mukhopadhyay1, Arash Chitsazan1, Lois Balmer2,3, Grant Morahan2, Graeme J Walker1†* 1Drug Discovery Group, QIMR Berghofer Medical Research Institute, Herston, Australia; 2Centre for Diabetes Research, Harry Perkins Institute of Medical Research, Perth, Australia; 3School of Medical and Health Sciences, Edith Cowan University, Joondalup, Australia Abstract Genetic variation conferring resistance and susceptibility to carcinogen-induced tumorigenesis is frequently studied in mice. We have now turned this idea to melanoma using the collaborative cross (CC), a resource of mouse strains designed to discover genes for complex diseases. We studied melanoma-prone transgenic progeny across seventy CC genetic backgrounds. We mapped a strong quantitative trait locus for rapid onset spontaneous melanoma onset to Prkdc, a gene involved in detection and repair of DNA damage. In contrast, rapid onset UVR-induced melanoma was linked to the ribosomal subunit gene Rrp15. Ribosome biogenesis was upregulated in skin shortly after UVR exposure. Mechanistically, variation in the ‘usual suspects’ by which UVR may exacerbate melanoma, defective DNA repair, melanocyte proliferation, or inflammatory cell infiltration, did not explain melanoma susceptibility or resistance across the CC. *For correspondence: [email protected] Instead, events occurring soon after exposure, such as dysregulation of ribosome function, which alters many aspects of cellular metabolism, may be important. † Present address: Experimental DOI: https://doi.org/10.7554/eLife.42424.001 Dermatology Group, The University of Queensland Diamantina Institute, Woolloongabba, Australia Introduction Competing interests: The Cutaneous malignant melanoma (MM) is well known to be associated with high levels of sun expo- authors declare that no sure. -
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. -
A Molecular and Genetic Analysis of Otosclerosis
A molecular and genetic analysis of otosclerosis Joanna Lauren Ziff Submitted for the degree of PhD University College London January 2014 1 Declaration I, Joanna Ziff, confirm that the work presented in this thesis is my own. Where information has been derived from other sources, I confirm that this has been indicated in the thesis. Where work has been conducted by other members of our laboratory, this has been indicated by an appropriate reference. 2 Abstract Otosclerosis is a common form of conductive hearing loss. It is characterised by abnormal bone remodelling within the otic capsule, leading to formation of sclerotic lesions of the temporal bone. Encroachment of these lesions on to the footplate of the stapes in the middle ear leads to stapes fixation and subsequent conductive hearing loss. The hereditary nature of otosclerosis has long been recognised due to its recurrence within families, but its genetic aetiology is yet to be characterised. Although many familial linkage studies and candidate gene association studies to investigate the genetic nature of otosclerosis have been performed in recent years, progress in identifying disease causing genes has been slow. This is largely due to the highly heterogeneous nature of this condition. The research presented in this thesis examines the molecular and genetic basis of otosclerosis using two next generation sequencing technologies; RNA-sequencing and Whole Exome Sequencing. RNA–sequencing has provided human stapes transcriptomes for healthy and diseased stapes, and in combination with pathway analysis has helped identify genes and molecular processes dysregulated in otosclerotic tissue. Whole Exome Sequencing has been employed to investigate rare variants that segregate with otosclerosis in affected families, and has been followed by a variant filtering strategy, which has prioritised genes found to be dysregulated during RNA-sequencing. -
4-6 Weeks Old Female C57BL/6 Mice Obtained from Jackson Labs Were Used for Cell Isolation
Methods Mice: 4-6 weeks old female C57BL/6 mice obtained from Jackson labs were used for cell isolation. Female Foxp3-IRES-GFP reporter mice (1), backcrossed to B6/C57 background for 10 generations, were used for the isolation of naïve CD4 and naïve CD8 cells for the RNAseq experiments. The mice were housed in pathogen-free animal facility in the La Jolla Institute for Allergy and Immunology and were used according to protocols approved by the Institutional Animal Care and use Committee. Preparation of cells: Subsets of thymocytes were isolated by cell sorting as previously described (2), after cell surface staining using CD4 (GK1.5), CD8 (53-6.7), CD3ε (145- 2C11), CD24 (M1/69) (all from Biolegend). DP cells: CD4+CD8 int/hi; CD4 SP cells: CD4CD3 hi, CD24 int/lo; CD8 SP cells: CD8 int/hi CD4 CD3 hi, CD24 int/lo (Fig S2). Peripheral subsets were isolated after pooling spleen and lymph nodes. T cells were enriched by negative isolation using Dynabeads (Dynabeads untouched mouse T cells, 11413D, Invitrogen). After surface staining for CD4 (GK1.5), CD8 (53-6.7), CD62L (MEL-14), CD25 (PC61) and CD44 (IM7), naïve CD4+CD62L hiCD25-CD44lo and naïve CD8+CD62L hiCD25-CD44lo were obtained by sorting (BD FACS Aria). Additionally, for the RNAseq experiments, CD4 and CD8 naïve cells were isolated by sorting T cells from the Foxp3- IRES-GFP mice: CD4+CD62LhiCD25–CD44lo GFP(FOXP3)– and CD8+CD62LhiCD25– CD44lo GFP(FOXP3)– (antibodies were from Biolegend). In some cases, naïve CD4 cells were cultured in vitro under Th1 or Th2 polarizing conditions (3, 4). -
Integrated Analysis of Differentially Expressed Genes in Breast Cancer Pathogenesis
2560 ONCOLOGY LETTERS 9: 2560-2566, 2015 Integrated analysis of differentially expressed genes in breast cancer pathogenesis DAOBAO CHEN and HONGJIAN YANG Department of Breast Surgery, Zhejiang Cancer Hospital, Hangzhou, Zhejiang 310022, P.R. China Received October 20, 2014; Accepted March 10, 2015 DOI: 10.3892/ol.2015.3147 Abstract. The present study aimed to detect the differences ducts or from the lobules that supply the ducts (1). Breast between breast cancer cells and normal breast cells, and inves- cancer affects ~1.2 million women worldwide and accounts tigate the potential pathogenetic mechanisms of breast cancer. for ~50,000 mortalities every year (2). Despite major advances The sample GSE9574 series was downloaded, and the micro- in surgical and nonsurgical management of the disease, breast array data was analyzed to identify differentially expressed cancer metastasis remains a significant clinical challenge genes (DEGs). Gene Ontology (GO) cluster analysis using affecting numerous of patients (3). The prognosis and survival the GO Enrichment Analysis Software Toolkit platform and rates for breast cancer are highly variable, and depend on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway the cancer type, treatment strategy, stage of the disease and analysis for DEGs was conducted using the Gene Set Analysis geographical location of the patient (4). Toolkit V2. In addition, a protein-protein interaction (PPI) Microarray technology, which may be used to simultane- network was constructed, and target sites of potential transcrip- ously interrogate 10,000-40,000 genes, has provided new tion factors and potential microRNA (miRNA) molecules were insight into the molecular classification of different cancer screened. -
Yeast Genome Gazetteer P35-65
gazetteer Metabolism 35 tRNA modification mitochondrial transport amino-acid metabolism other tRNA-transcription activities vesicular transport (Golgi network, etc.) nitrogen and sulphur metabolism mRNA synthesis peroxisomal transport nucleotide metabolism mRNA processing (splicing) vacuolar transport phosphate metabolism mRNA processing (5’-end, 3’-end processing extracellular transport carbohydrate metabolism and mRNA degradation) cellular import lipid, fatty-acid and sterol metabolism other mRNA-transcription activities other intracellular-transport activities biosynthesis of vitamins, cofactors and RNA transport prosthetic groups other transcription activities Cellular organization and biogenesis 54 ionic homeostasis organization and biogenesis of cell wall and Protein synthesis 48 plasma membrane Energy 40 ribosomal proteins organization and biogenesis of glycolysis translation (initiation,elongation and cytoskeleton gluconeogenesis termination) organization and biogenesis of endoplasmic pentose-phosphate pathway translational control reticulum and Golgi tricarboxylic-acid pathway tRNA synthetases organization and biogenesis of chromosome respiration other protein-synthesis activities structure fermentation mitochondrial organization and biogenesis metabolism of energy reserves (glycogen Protein destination 49 peroxisomal organization and biogenesis and trehalose) protein folding and stabilization endosomal organization and biogenesis other energy-generation activities protein targeting, sorting and translocation vacuolar and lysosomal -
Nucleolin and Its Role in Ribosomal Biogenesis
NUCLEOLIN: A NUCLEOLAR RNA-BINDING PROTEIN INVOLVED IN RIBOSOME BIOGENESIS Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf vorgelegt von Julia Fremerey aus Hamburg Düsseldorf, April 2016 2 Gedruckt mit der Genehmigung der Mathematisch-Naturwissenschaftlichen Fakultät der Heinrich-Heine-Universität Düsseldorf Referent: Prof. Dr. A. Borkhardt Korreferent: Prof. Dr. H. Schwender Tag der mündlichen Prüfung: 20.07.2016 3 Die vorgelegte Arbeit wurde von Juli 2012 bis März 2016 in der Klinik für Kinder- Onkologie, -Hämatologie und Klinische Immunologie des Universitätsklinikums Düsseldorf unter Anleitung von Prof. Dr. A. Borkhardt und in Kooperation mit dem ‚Laboratory of RNA Molecular Biology‘ an der Rockefeller Universität unter Anleitung von Prof. Dr. T. Tuschl angefertigt. 4 Dedicated to my family TABLE OF CONTENTS 5 TABLE OF CONTENTS TABLE OF CONTENTS ............................................................................................... 5 LIST OF FIGURES ......................................................................................................10 LIST OF TABLES .......................................................................................................12 ABBREVIATION .........................................................................................................13 ABSTRACT ................................................................................................................19 ZUSAMMENFASSUNG -
Enzymes and Rna Complexes
ENZYMES AND RNA COMPLEXES Mediator NMD Exosome NMD TRAMP/NNS Integrator Microprocessor RNA PROCESSING and DECAY machinery: RNases Protein Function Characteristics Exonucleases 5’ 3’ Xrn1 cytoplasmic, mRNA degradation processsive Rat1 nuclear, pre-rRNA, sn/snoRNA, pre-mRNA processing and degradation Rrp17/hNol12 nuclear, pre-rRNA processing Exosome 3’ 5’ multisubunit exo/endo complex subunits organized as in bacterial PNPase Rrp44/Dis3 catalytic subunit Exo/PIN domains, processsive Rrp4, Rrp40 pre-rRNA, sn/snoRNA processing, mRNA degradation Rrp41-43, 45-46 participates in NMD, ARE-dependent, non-stop decay Mtr3, Ski4 Mtr4 nuclear helicase cofactor DEAD box Rrp6 (Rrp47) nuclear exonuclease ( Rrp6 BP, cofactor) RNAse D homolog, processsive Ski2,3,7,8 cytoplasmic exosome cofactors. SKI complex helicase, GTPase Other 3’ 5’ Rex1-4 3’-5’ exonucleases, rRNA, snoRNA, tRNA processing RNase D homolog DXO 3’-5’ exonuclease in addition to decapping mtEXO 3’ 5’ mitochondrial degradosome RNA degradation in yeast Suv3/ Dss1 helicase/ 3’-5’ exonuclease DExH box/ RNase II homolog Deadenylation Ccr4/NOT/Pop2 major deadenylase complex (Ccr, Caf, Pop, Not proteins) Ccr4- Mg2+ dependent endonuclease Pan2p/Pan3 additional deadenylases (poliA tail length) RNase D homolog, poly(A) specific nuclease PARN mammalian deadenylase RNase D homolog, poly(A) specific nuclease Endonucleases RNase III -Rnt1 pre-rRNA, sn/snoRNA processing, mRNA degradation dsRNA specific -Dicer, Drosha siRNA/miRNA biogenesis, functions in RNAi PAZ, RNA BD, RNase III domains Ago2 Slicer -
A Disease-Linked Lncrna Mutation in Rnase MRP Inhibits Ribosome Synthesis
bioRxiv preprint doi: https://doi.org/10.1101/2021.03.29.437572; this version posted March 29, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. A disease-linked lncRNA mutation in RNase MRP inhibits ribosome synthesis Nic Roberston1, Vadim Shchepachev1, David Wright2, Tomasz W. Turowski1, Christos Spanos1, Aleksandra Helwak1, Rose Zamoyska2, David Tollervey1 1 Wellcome Centre for Cell Biology, University of Edinburgh, Edinburgh, UK 2 Ashworth Laboratories, Institute of Immunology and Infection Research, University of Edinburgh, Edinburgh, UK Keywords: protein-RNA interaction; RNA-binding sites; UV crosslinking; mass spectrometry; genetic disease; Cartilage Hair Hypoplasia; ribosome synthesis; T cell activation Running title: RNase MRP defects cause ribosomopathy Highlights: • Mutations in RMRP lncRNA impair pre-rRNA processing and T cell activation • Patient derived fibroblasts show impaired pre-rRNA processing • Cells with the most common disease-linked mutation have specific processing defects • Cytoplasmic ribosomes and intact RNase MRP complexes are also reduced in these cells 1 bioRxiv preprint doi: https://doi.org/10.1101/2021.03.29.437572; this version posted March 29, 2021. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Abstract Mutations in the human RMRP gene cause Cartilage Hair Hypoplasia (CHH), an autosomal recessive disorder characterized by skeletal abnormalities and impaired T cell activation. -
Differences in Aggressive Behavior and DNA Copy Number Variants Between BALB/Cj and BALB/Cbyj Substrains
Behav Genet (2010) 40:201–210 DOI 10.1007/s10519-009-9325-5 ORIGINAL RESEARCH Differences in Aggressive Behavior and DNA Copy Number Variants Between BALB/cJ and BALB/cByJ Substrains Lady Velez • Greta Sokoloff • Klaus A. Miczek • Abraham A. Palmer • Stephanie C. Dulawa Received: 3 February 2009 / Accepted: 3 December 2009 / Published online: 23 December 2009 Ó Springer Science+Business Media, LLC 2009 Abstract Some BALB/c substrains exhibit different Keywords Aggression Á Resident intruder Á BALB/c Á levels of aggression. We compared aggression levels CNV Á Substrain between male BALB/cJ and BALB/cByJ substrains using the resident intruder paradigm. These substrains were also assessed in other tests of emotionality and information Introduction processing including the open field, forced swim, fear conditioning, and prepulse inhibition tests. We also eval- Some substrains of BALB/c mice have previously been uated single nucleotide polymorphisms (SNPs) previously suggested to exhibit robust differences in aggressive reported between these BALB/c substrains. Finally, we behavior, although the genetic basis for this behavioral dif- compared BALB/cJ and BALB/cByJ mice for genomic ference has not been identified (Ciaranello et al. 1974). The deletions or duplications, collectively termed copy number BALB/c substrains were derived from an initial BALB/c variants (CNVs), to identify candidate genes that might stock established by 1935 (Les 1990); this BALB/c stock underlie the observed behavioral differences. BALB/cJ was then acquired by several other laboratories and were mice showed substantially higher aggression levels than maintained and bred as independent stocks including BALB/ BALB/cByJ mice; however, only minor differences in cJ, BALB/cN, and BALB/cByJ. -
“The Impact of ART on Genome‐Wide Oxidation of 5‐Methylcytosine and the Transcriptome During Early Mouse Development”
“The impact of ART on genome‐wide oxidation of 5‐methylcytosine and the transcriptome during early mouse development” Dissertation zur Erlangung des Grades “Doktor der Naturwissenschaften” am Fachbereich Biologie der Johannes Gutenberg-Universität Mainz Elif Diken geb. Söğütcü geb. am 22.07.1987 in Giresun-TURKEY Mainz 2016 Dekan: 1. Berichterstatter: 2. Berichterstatter: Tag der mündlichen Prüfung: Summary Summary The use of assisted reproductive technologies (ART) has been increasing over the past three decades due to the elevated frequency of infertility problems. Other factors such as easier access to medical aid than in the past and its coverage by health insurance companies in many developed countries also contributed to this growing interest. Nevertheless, a negative impact of ART on transcriptome and methylation reprogramming is heavily discussed. Methylation reprogramming directly after fertilization manifests itself as genome-wide DNA demethylation associated with the oxidation of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) in the pronuclei of mouse zygotes. To investigate the possible impact of ART particularly on this process and the transcriptome in general, pronuclear stage mouse embryos obtained upon spontaneous ovulation or superovulation through hormone stimulation representing ART were subjected to various epigenetic analyses. A whole- transcriptome RNA-Seq analysis of pronuclear stage embryos from spontaneous and superovulated matings demonstrated altered expression of the Bbs12 gene known to be linked to Bardet-Biedl syndrome (BBS) as well as the Dhx16 gene whose zebrafish ortholog was reported to be a maternal effect gene. Immunofluorescence staining with antibodies against 5mC and 5hmC showed that pronuclear stage embryos obtained by superovulation have an increased incidence of abnormal methylation and hydroxymethylation patterns in both maternal and paternal pronuclear DNA compared to their spontaneously ovulated counterparts. -
Supplementary Table S4. FGA Co-Expressed Gene List in LUAD
Supplementary Table S4. FGA co-expressed gene list in LUAD tumors Symbol R Locus Description FGG 0.919 4q28 fibrinogen gamma chain FGL1 0.635 8p22 fibrinogen-like 1 SLC7A2 0.536 8p22 solute carrier family 7 (cationic amino acid transporter, y+ system), member 2 DUSP4 0.521 8p12-p11 dual specificity phosphatase 4 HAL 0.51 12q22-q24.1histidine ammonia-lyase PDE4D 0.499 5q12 phosphodiesterase 4D, cAMP-specific FURIN 0.497 15q26.1 furin (paired basic amino acid cleaving enzyme) CPS1 0.49 2q35 carbamoyl-phosphate synthase 1, mitochondrial TESC 0.478 12q24.22 tescalcin INHA 0.465 2q35 inhibin, alpha S100P 0.461 4p16 S100 calcium binding protein P VPS37A 0.447 8p22 vacuolar protein sorting 37 homolog A (S. cerevisiae) SLC16A14 0.447 2q36.3 solute carrier family 16, member 14 PPARGC1A 0.443 4p15.1 peroxisome proliferator-activated receptor gamma, coactivator 1 alpha SIK1 0.435 21q22.3 salt-inducible kinase 1 IRS2 0.434 13q34 insulin receptor substrate 2 RND1 0.433 12q12 Rho family GTPase 1 HGD 0.433 3q13.33 homogentisate 1,2-dioxygenase PTP4A1 0.432 6q12 protein tyrosine phosphatase type IVA, member 1 C8orf4 0.428 8p11.2 chromosome 8 open reading frame 4 DDC 0.427 7p12.2 dopa decarboxylase (aromatic L-amino acid decarboxylase) TACC2 0.427 10q26 transforming, acidic coiled-coil containing protein 2 MUC13 0.422 3q21.2 mucin 13, cell surface associated C5 0.412 9q33-q34 complement component 5 NR4A2 0.412 2q22-q23 nuclear receptor subfamily 4, group A, member 2 EYS 0.411 6q12 eyes shut homolog (Drosophila) GPX2 0.406 14q24.1 glutathione peroxidase