Mitochondrial Gene Expression and Beyond—Novel Aspects of Cellular Physiology
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TRNT1 Gene Trna Nucleotidyl Transferase 1
TRNT1 gene tRNA nucleotidyl transferase 1 Normal Function The TRNT1 gene provides instructions for making a protein involved in the production ( synthesis) of other proteins. During protein synthesis, a molecule called transfer RNA ( tRNA) helps assemble protein building blocks (amino acids) into a chain that forms the protein. Each tRNA carries a specific amino acid to the growing chain. The TRNT1 protein modifies tRNAs by adding a series of three DNA building blocks (nucleotides), called a CCA trinucleotide, to the molecule. This modification is essential for the correct amino acid to be attached to each tRNA. While most protein synthesis occurs in the fluid surrounding the nucleus (cytoplasm), some proteins are synthesized in cell structures called mitochondria, which are the energy-producing centers in cells. Many mitochondrial proteins form groups (complexes) that carry out the reactions that produce energy. Separate tRNA molecules are used to build proteins in the cytoplasm and mitochondria. The TRNT1 protein attaches the CCA trinucleotide to both cytoplasmic and mitochondrial tRNA molecules. Health Conditions Related to Genetic Changes TRNT1 deficiency More than 20 TRNT1 gene mutations have been found to cause TRNT1 deficiency, a condition with a range of signs and symptoms that affect many body systems. Features can include a blood disorder called sideroblastic anemia, recurrent fevers, a shortage of immune cells called B cells that leads to impairment of the immune system ( immunodeficiency), delayed development of speech and motor skills, and eye abnormalities that cause vision problems. The severity of the condition varies among affected individuals. The TRNT1 gene mutations that cause TRNT1 deficiency lead to a shortage (deficiency) of functional TRNT1 protein. -
Table 2. Significant
Table 2. Significant (Q < 0.05 and |d | > 0.5) transcripts from the meta-analysis Gene Chr Mb Gene Name Affy ProbeSet cDNA_IDs d HAP/LAP d HAP/LAP d d IS Average d Ztest P values Q-value Symbol ID (study #5) 1 2 STS B2m 2 122 beta-2 microglobulin 1452428_a_at AI848245 1.75334941 4 3.2 4 3.2316485 1.07398E-09 5.69E-08 Man2b1 8 84.4 mannosidase 2, alpha B1 1416340_a_at H4049B01 3.75722111 3.87309653 2.1 1.6 2.84852656 5.32443E-07 1.58E-05 1110032A03Rik 9 50.9 RIKEN cDNA 1110032A03 gene 1417211_a_at H4035E05 4 1.66015788 4 1.7 2.82772795 2.94266E-05 0.000527 NA 9 48.5 --- 1456111_at 3.43701477 1.85785922 4 2 2.8237185 9.97969E-08 3.48E-06 Scn4b 9 45.3 Sodium channel, type IV, beta 1434008_at AI844796 3.79536664 1.63774235 3.3 2.3 2.75319499 1.48057E-08 6.21E-07 polypeptide Gadd45gip1 8 84.1 RIKEN cDNA 2310040G17 gene 1417619_at 4 3.38875643 1.4 2 2.69163229 8.84279E-06 0.0001904 BC056474 15 12.1 Mus musculus cDNA clone 1424117_at H3030A06 3.95752801 2.42838452 1.9 2.2 2.62132809 1.3344E-08 5.66E-07 MGC:67360 IMAGE:6823629, complete cds NA 4 153 guanine nucleotide binding protein, 1454696_at -3.46081884 -4 -1.3 -1.6 -2.6026947 8.58458E-05 0.0012617 beta 1 Gnb1 4 153 guanine nucleotide binding protein, 1417432_a_at H3094D02 -3.13334396 -4 -1.6 -1.7 -2.5946297 1.04542E-05 0.0002202 beta 1 Gadd45gip1 8 84.1 RAD23a homolog (S. -
Transcriptional Requirements of the Distal Heavy-Strand Promoter of Mtdna
Transcriptional requirements of the distal heavy-strand promoter of mtDNA Ornella Zolloa, Valeria Tirantib, and Neal Sondheimera,c,1 aDivision of Child Rehabilitation, The Children’s Hospital of Philadelphia and cDepartment of Pediatrics, University of Pennsylvania, Philadelphia, PA 19104; and bDivision of Molecular Neurogenetics, Foundation Neurological Institute “C. Besta”, 20126 Milan, Italy Edited* by Douglas C. Wallace, Center for Mitochondrial and Epigenomic Medicine, Children’s Hospital of Philadelphia, Philadelphia, PA, and approved March 6, 2012 (received for review November 12, 2011) The heavy strand of mtDNA contains two promoters with non- HSP2 in cells was precisely mapped to C646 using primer ex- overlapping functions. The role of the minor heavy-strand pro- tension and S1 digest of nascent transcripts from HeLa cells (7). moter (HSP2) is controversial, because the promoter has been However, recent studies that examined the minimal set of pro- difficult to activate in an in vitro system. We have isolated HSP2 by teins required for mitochondrial transcription in vitro were un- excluding its interaction with the more powerful HSP1 promoter, able to identify any transcription arising from HSP2 (8, 9). To and we find that it is transcribed efficiently by recombinant resolve this apparent conflict, we investigated transcription from mtRNA polymerase and mitochondrial transcription factor B2. The HSP2 in vitro using recombinant proteins and HeLa cell mito- mitochondrial transcription factor A is not required for initiation, chondrial extracts. We find that the promoter is active, responsive but it has the ability to alternatively activate and repress the HSP2 to mitochondrial transcription factor A (TFAM) dosage, and transcriptional unit depending on the ratio between mitochon- sensitive to mutations in upstream sequence. -
Unravelling the Cellular Origin and Clinical Prognostic Markers of Infant
Published Ahead of Print on January 24, 2019, as doi:10.3324/haematol.2018.206375. Copyright 2019 Ferrata Storti Foundation. Unravelling the cellular origin and clinical prognostic markers of infant B-cell acute lymphoblastic leukemia using genome-wide analysis by Antonio Agraz-Doblas, Clara Bueno, Rachael Bashford-Rogers, Anindita Roy, Pauline Schneider, Michela Bardini, Paola Ballerini, Gianni Cazzaniga, Thaidy Moreno, Carlos Revilla, Marta Gut, Maria G Valsecchi, Irene Roberts, Rob Pieters, Paola De Lorenzo, Ignacio Varela, Pablo Menendez, and Ronald W Stam Haematologica 2019 [Epub ahead of print] Citation: Antonio Agraz-Doblas, Clara Bueno, Rachael Bashford-Rogers, Anindita Roy, Pauline Schneider, Michela Bardini, Paola Ballerini, Gianni Cazzaniga, Thaidy Moreno, Carlos Revilla, Marta Gut, Maria G Valsecchi, Irene Roberts, Rob Pieters, Paola De Lorenzo, Ignacio Varela, Pablo Menendez, and Ronald W Stam. Unravelling the cellular origin and clinical prognostic markers of infant B-cell acute lymphoblastic leukemia using genome-wide analysis Haematologica. 2019; 104:xxx doi:10.3324/haematol.2018.206375 Publisher's Disclaimer. E-publishing ahead of print is increasingly important for the rapid dissemination of science. Haematologica is, therefore, E-publishing PDF files of an early version of manuscripts that have completed a regular peer review and have been accepted for publication. E-publishing of this PDF file has been approved by the authors. After having E-published Ahead of Print, manuscripts will then undergo technical and English editing, typesetting, proof correction and be presented for the authors' final approval; the final version of the manuscript will then appear in print on a regular issue of the journal. All legal disclaimers that apply to the journal also pertain to this production process. -
Gene Therapy Glossary of Terms
GENE THERAPY GLOSSARY OF TERMS A • Phase 3: A phase of research to describe clinical trials • Allele: one of two or more alternative forms of a gene that that gather more information about a drug’s safety and arise by mutation and are found at the same place on a effectiveness by studying different populations and chromosome. different dosages and by using the drug in combination • Adeno-Associated Virus: A single stranded DNA virus that has with other drugs. These studies typically involve more not been found to cause disease in humans. This type of virus participants.7 is the most frequently used in gene therapy.1 • Phase 4: A phase of research to describe clinical trials • Adenovirus: A member of a family of viruses that can cause occurring after FDA has approved a drug for marketing. infections in the respiratory tract, eye, and gastrointestinal They include post market requirement and commitment tract. studies that are required of or agreed to by the study • Adeno-Associated Virus Vector: Adeno viruses used as sponsor. These trials gather additional information about a vehicles for genes, whose core genetic material has been drug’s safety, efficacy, or optimal use.8 removed and replaced by the FVIII- or FIX-gene • Codon: a sequence of three nucleotides in DNA or RNA • Amino Acids: building block of a protein that gives instructions to add a specific amino acid to an • Antibody: a protein produced by immune cells called B-cells elongating protein in response to a foreign molecule; acts by binding to the • CRISPR: a family of DNA sequences that can be cleaved by molecule and often making it inactive or targeting it for specific enzymes, and therefore serve as a guide to cut out destruction and insert genes. -
Zhou Et Al POLQ Inhibitor.Docx
bioRxiv preprint doi: https://doi.org/10.1101/2020.05.23.111658; this version posted May 26, 2020. 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-NC-ND 4.0 International license. Polymerase Theta Inhibition Kills Homologous Recombination Deficient Tumors Jia Zhou1, Camille Gelot2, Constantia Pantelidou3, Adam Li1, Hatice Yücel2, Rachel E. Davis4, Anniina Farkkila1, Bose Kochupurakkal1, Aleem Syed5, Geoffrey I. Shapiro3,6, John A. Tainer5, Brian S. J. Blagg4, Raphael Ceccaldi2,7* and Alan D. D’Andrea1,6,7* 1Department of Radiation Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02215, USA. 2Inserm U830, PSL Research University, Institut Curie, 75005, Paris, France. 3Department of Medical Oncology, Dana-Farber Cancer Institute and Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. 4Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556, USA. 5Departments of Cancer Biology and of Molecular and Cellular Oncology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA. 6Center for DNA Damage and Repair, Dana-Farber Cancer Institute, Boston, MA, USA. 7Co-senior authors. * Co-corresponding authors. * Corresponding authors: Alan D. D’Andrea, M.D. Director, Susan F. Smith Center for Women’s Cancers (SFSCWC) Director, Center for DNA Damage and Repair Dana-Farber Cancer Institute The Fuller-American Cancer Society Professor Harvard Medical School Phone: 617-632-2080 Email: [email protected] Raphael Ceccaldi Institut Curie, 75005, Paris, France Phone: +33 (0)1 56 24 69 49 Email: [email protected] Key Words: Novobiocin, Polymerase theta (POLθ), Homologous Recombination, PARP inhibitor resistance. -
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. -
Re-Coding the ‘Corrupt’ Code: CRISPR-Cas9 Interventions in Human Germ Line Editing
Re-coding the ‘corrupt’ code: CRISPR-Cas9 interventions in human germ line editing CRISPR-Cas9, Germline Intervention, Human Cognition, Human Rights, International Regulation Master Thesis Tilburg University- Law and Technology 2018-19 Tilburg Institute for Law, Technology, and Society (TILT) October 2019 Student: Srishti Tripathy Supervisors: Prof. Dr. Robin Pierce SRN: 2012391 Dr. Emre Bayamlioglu ANR: 659785 Re-coding the ‘corrupt’ code CRISPR-Cas9, Germline Intervention, Human Cognition, Human Rights, International Regulation This page is intentionally left blank 2 Re-coding the ‘corrupt’ code CRISPR-Cas9, Germline Intervention, Human Cognition, Human Rights, International Regulation 3 Re-coding the ‘corrupt’ code CRISPR-Cas9, Germline Intervention, Human Cognition, Human Rights, International Regulation Table of Contents CHAPTER 1: Introduction .............................................................................................................. 6 1.1 Introduction and Review - “I think I’m crazy enough to do it” ......................................................................... 6 1.2 Research Question and Sub Questions .......................................................................................................................... 9 1.4 Methodology ............................................................................................................................................................................. 9 1.4 Thesis structure: ................................................................................................................................................................. -
Download Validation Data
PrimePCR™Assay Validation Report Gene Information Gene Name FAST kinase domain-containing protein 1 Gene Symbol Fastkd1 Organism Rat Gene Summary Description Not Available Gene Aliases Not Available RefSeq Accession No. NM_001191738 UniGene ID Rn.226110 Ensembl Gene ID ENSRNOG00000024335 Entrez Gene ID 311112 Assay Information Unique Assay ID qRnoCEP0034063 Assay Type Probe - Validation information is for the primer pair using SYBR® Green detection Detected Coding Transcript(s) ENSRNOT00000036585 Amplicon Context Sequence AAAAAAAAAAACTACAGTCATGATCTGCCTGCTCCAAATATCTGTTCTCTCAGGTA GTCCATCCGTGTATCCTTCGTTGACATTGCCATGGAGTTCCA Amplicon Length (bp) 68 Chromosome Location 3:62537455-62537552 Assay Design Exonic Purification Desalted Validation Results Efficiency (%) 97 R2 0.9997 cDNA Cq 23.19 cDNA Tm (Celsius) 79 gDNA Cq Specificity (%) 100 Information to assist with data interpretation is provided at the end of this report. Page 1/4 PrimePCR™Assay Validation Report Fastkd1, Rat Amplification Plot Amplification of cDNA generated from 25 ng of universal reference RNA Melt Peak Melt curve analysis of above amplification Standard Curve Standard curve generated using 20 million copies of template diluted 10-fold to 20 copies Page 2/4 PrimePCR™Assay Validation Report Products used to generate validation data Real-Time PCR Instrument CFX384 Real-Time PCR Detection System Reverse Transcription Reagent iScript™ Advanced cDNA Synthesis Kit for RT-qPCR Real-Time PCR Supermix SsoAdvanced™ SYBR® Green Supermix Experimental Sample qPCR Reference Total RNA Data Interpretation Unique Assay ID This is a unique identifier that can be used to identify the assay in the literature and online. Detected Coding Transcript(s) This is a list of the Ensembl transcript ID(s) that this assay will detect. Details for each transcript can be found on the Ensembl website at www.ensembl.org. -
Zinc Fingers and a Green Thumb: Manipulating Gene Expression in Plants Segal, Stege and Barbas 165
163 Zinc fingers and a green thumb: manipulating gene expression in plants David J Segaly, Justin T Stegez and Carlos F Barbas IIIç Artificial transcription factors can be rapidly constructed A variety of techniques have been developed to manip- from predefined zinc-finger modules to regulate virtually any ulate gene expression in plants. Increased expression of gene. Stable, heritable up- and downregulation of endogenous genes is most commonly achieved through endogenous genes has been demonstrated in transgenic transgene overexpression [1]. The introduction of tissue- plants. These advances promise new approaches for creating specific and inducible promoters has improved the utility functional knockouts and conditional overexpression, and of this approach, and efficient and robust plant transforma- for other gene discovery and manipulation applications in tion techniques have made the construction of transgenes plants. a relatively routine task. However, variable expression and co-suppression of transgenes often complicate this process. Addresses Furthermore, transgenes cannot accommodate alternative ÃThe Skaggs Institute for Chemical Biology and the Department of splicing, which may be important for the appropriate Molecular Biology, The Scripps Research Institute, La Jolla, function of some transgenes [2]. California 92037, USA yDepartment of Pharmacology and Toxicology, University of Arizona, Tucson, Arizona 85721, USA Reducing or eliminating the expression of a gene in plants zDiversa Corporation, San Diego, California 92121, USA is not as simple as overexpressing a gene. Gene disruption §The Scripps Research Institute, BCC-550, North Torrey Pines Road, by homologous recombination, tDNA insertions and che- La Jolla, California 92037, USA mical mutagenesis has been used successfully, but these e-mail: [email protected] Correspondence: Carlos F Barbas III approaches are inefficient and time-consuming technolo- gies. -
COMMENTARY Does Transcription by RNA Polymerase Play a Direct Role in the Initiation of Replication?
Journal of Cell Science 107, 1381-1387 (1994) 1381 Printed in Great Britain © The Company of Biologists Limited 1994 COMMENTARY Does transcription by RNA polymerase play a direct role in the initiation of replication? A. Bassim Hassan* and Peter R. Cook† CRC Nuclear Structure and Function Research Group, Sir William Dunn School of Pathology, University of Oxford, South Parks Road, Oxford, UK *Present address: Addenbrooke’s NHS Trust, Hills Rd, Cambridge CB2 2QQ, UK †Author for correspondence SUMMARY RNA polymerases have been implicated in the initiation of replication in bacteria. The conflicting evidence for a role in initiation in eukaryotes is reviewed. Key words: cell cycle, initiation, origin, replication, transcription PRIMERS AND PRIMASES complex becomes exclusively involved in the synthesis of Okazaki fragments on the lagging strand. A critical step in this DNA polymerases cannot initiate the synthesis of new DNA process is the unwinding of the duplex. chains, they can only elongate pre-existing primers. The opposite polarities of the two strands of the double helix coupled with the 5′r3′ polarity of the polymerase means that RNA POLYMERASES AND THE INITIATION OF replication occurs relatively continuously on one (leading) REPLICATION IN BACTERIA strand and discontinuously on the other (lagging) strand. The continuous strand probably needs to be primed once, usually The first evidence of a role for RNA polymerase came from at an origin. Nature has found many different ways of doing the demonstration that the initiation of replication in this, including the use of RNA primers made by an RNA poly- Escherichia coli was sensitive to rifampicin, an inhibitor of merase (e.g. -
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)