NSUN2 Introduces 5-Methylcytosines in Mammalian Mitochondrial Trnas
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Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach
Mafalda Rita Avó Bacalhau Establishing the Pathogenicity of Novel Mitochondrial DNA Sequence Variations: a Cell and Molecular Biology Approach Tese de doutoramento do Programa de Doutoramento em Ciências da Saúde, ramo de Ciências Biomédicas, orientada pela Professora Doutora Maria Manuela Monteiro Grazina e co-orientada pelo Professor Doutor Henrique Manuel Paixão dos Santos Girão e pela Professora Doutora Lee-Jun C. Wong e apresentada à Faculdade de Medicina da Universidade de Coimbra Julho 2017 Faculty of Medicine Establishing the pathogenicity of novel mitochondrial DNA sequence variations: a cell and molecular biology approach Mafalda Rita Avó Bacalhau Tese de doutoramento do programa em Ciências da Saúde, ramo de Ciências Biomédicas, realizada sob a orientação científica da Professora Doutora Maria Manuela Monteiro Grazina; e co-orientação do Professor Doutor Henrique Manuel Paixão dos Santos Girão e da Professora Doutora Lee-Jun C. Wong, apresentada à Faculdade de Medicina da Universidade de Coimbra. Julho, 2017 Copyright© Mafalda Bacalhau e Manuela Grazina, 2017 Esta cópia da tese é fornecida na condição de que quem a consulta reconhece que os direitos de autor são pertença do autor da tese e do orientador científico e que nenhuma citação ou informação obtida a partir dela pode ser publicada sem a referência apropriada e autorização. This copy of the thesis has been supplied on the condition that anyone who consults it recognizes that its copyright belongs to its author and scientific supervisor and that no quotation from the -
By Submitted in Partial Satisfaction of the Requirements for Degree of in In
Developments of Two Imaging based Technologies for Cell Biology Researches by Xiaowei Yan DISSERTATION Submitted in partial satisfaction of the requirements for degree of DOCTOR OF PHILOSOPHY in Biochemistry and Molecular Biology in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, SAN FRANCISCO Approved: ______________________________________________________________________________Ronald Vale Chair ______________________________________________________________________________Jonathan Weissman ______________________________________________________________________________Orion Weiner ______________________________________________________________________________ ______________________________________________________________________________ Committee Members Copyright 2021 By Xiaowei Yan ii DEDICATION Everything happens for the best. To my family, who supported me with all their love. iii ACKNOWLEDGEMENTS The greatest joy of my PhD has been joining UCSF, working and learning with such a fantastic group of scientists. I am extremely grateful for all the support and mentorship I received and would like to thank: My mentor, Ron Vale, who is such a great and generous person. Thank you for showing me that science is so much fun and thank you for always giving me the freedom in pursuing my interest. I am grateful for all the guidance from you and thank you for always supporting me whenever I needed. You are a person full of wisdom, and I have been learning so much from you and your attitude to science, science community and even life will continue inspire me. Thank you for being my mentor and thank you for being such a great mentor. Everyone else in Vale lab, past and present, for making our lab a sweet home. I would like to give my special thank to Marvin (Marvin Tanenbaum) and Nico (Nico Stuurman), two other mentors for me in the lab. I would like to thank them for helping me adapt to our lab, for all the valuable advice and for all the happiness during the time that we work together. -
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. -
Epigenetic Mechanisms of Lncrnas Binding to Protein in Carcinogenesis
cancers Review Epigenetic Mechanisms of LncRNAs Binding to Protein in Carcinogenesis Tae-Jin Shin, Kang-Hoon Lee and Je-Yoel Cho * Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, School of Veterinary Medicine, Seoul National University, Seoul 08826, Korea; [email protected] (T.-J.S.); [email protected] (K.-H.L.) * Correspondence: [email protected]; Tel.: +82-02-800-1268 Received: 21 September 2020; Accepted: 9 October 2020; Published: 11 October 2020 Simple Summary: The functional analysis of lncRNA, which has recently been investigated in various fields of biological research, is critical to understanding the delicate control of cells and the occurrence of diseases. The interaction between proteins and lncRNA, which has been found to be a major mechanism, has been reported to play an important role in cancer development and progress. This review thus organized the lncRNAs and related proteins involved in the cancer process, from carcinogenesis to metastasis and resistance to chemotherapy, to better understand cancer and to further develop new treatments for it. This will provide a new perspective on clinical cancer diagnosis, prognosis, and treatment. Abstract: Epigenetic dysregulation is an important feature for cancer initiation and progression. Long non-coding RNAs (lncRNAs) are transcripts that stably present as RNA forms with no translated protein and have lengths larger than 200 nucleotides. LncRNA can epigenetically regulate either oncogenes or tumor suppressor genes. Nowadays, the combined research of lncRNA plus protein analysis is gaining more attention. LncRNA controls gene expression directly by binding to transcription factors of target genes and indirectly by complexing with other proteins to bind to target proteins and cause protein degradation, reduced protein stability, or interference with the binding of other proteins. -
METTL1 Promotes Let-7 Microrna Processing Via M7g Methylation
Article METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation Graphical Abstract Authors Luca Pandolfini, Isaia Barbieri, Andrew J. Bannister, ..., Mara d’Onofrio, Shankar Balasubramanian, Tony Kouzarides Correspondence [email protected] In Brief Pandolfini, Barbieri, et al. show that a subgroup of tumor suppressor microRNAs, including let-7e, contain 7-methylguanosine (m7G). Methyltransferase METTL1 is required for m7G modification of miRNAs, their efficient processing, and the inhibition of lung cancer cell migration. Structurally, m7G in miRNA precursors antagonizes RNA secondary structures that would otherwise inhibit their maturation. Highlights Data Resource d Internal m7G is identified in miRNAs by two independent GSE112182 sequencing techniques GSE112180 GSE112181 d Methyltransferase METTL1 mediates m7G modification of GSE120454 specific miRNAs GSE120455 d METTL1 promotes miRNA maturation and suppresses lung cancer cell migration d m7G promotes processing by antagonizing G-quadruplex structures in miRNA precursors Pandolfini et al., 2019, Molecular Cell 74, 1278–1290 June 20, 2019 ª 2019 The Author(s). Published by Elsevier Inc. https://doi.org/10.1016/j.molcel.2019.03.040 Molecular Cell Article METTL1 Promotes let-7 MicroRNA Processing via m7G Methylation Luca Pandolfini,1,9 Isaia Barbieri,1,2,9 Andrew J. Bannister,1 Alan Hendrick,3 Byron Andrews,3 Natalie Webster,3 Pierre Murat,4,7 Pia Mach,1 Rossella Brandi,5 Samuel C. Robson,1,8 Valentina Migliori,1 Andrej Alendar,1 Mara d’Onofrio,5,6 Shankar Balasubramanian,4 -
Análise Integrativa De Perfis Transcricionais De Pacientes Com
UNIVERSIDADE DE SÃO PAULO FACULDADE DE MEDICINA DE RIBEIRÃO PRETO PROGRAMA DE PÓS-GRADUAÇÃO EM GENÉTICA ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Ribeirão Preto – 2012 ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas Tese apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo para obtenção do título de Doutor em Ciências. Área de Concentração: Genética Orientador: Prof. Dr. Eduardo Antonio Donadi Co-orientador: Prof. Dr. Geraldo A. S. Passos Ribeirão Preto – 2012 AUTORIZO A REPRODUÇÃO E DIVULGAÇÃO TOTAL OU PARCIAL DESTE TRABALHO, POR QUALQUER MEIO CONVENCIONAL OU ELETRÔNICO, PARA FINS DE ESTUDO E PESQUISA, DESDE QUE CITADA A FONTE. FICHA CATALOGRÁFICA Evangelista, Adriane Feijó Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. Ribeirão Preto, 2012 192p. Tese de Doutorado apresentada à Faculdade de Medicina de Ribeirão Preto da Universidade de São Paulo. Área de Concentração: Genética. Orientador: Donadi, Eduardo Antonio Co-orientador: Passos, Geraldo A. 1. Expressão gênica – microarrays 2. Análise bioinformática por module maps 3. Diabetes mellitus tipo 1 4. Diabetes mellitus tipo 2 5. Diabetes mellitus gestacional FOLHA DE APROVAÇÃO ADRIANE FEIJÓ EVANGELISTA Análise integrativa de perfis transcricionais de pacientes com diabetes mellitus tipo 1, tipo 2 e gestacional, comparando-os com manifestações demográficas, clínicas, laboratoriais, fisiopatológicas e terapêuticas. -
Supplementary Materials
Supplementary materials Supplementary Table S1: MGNC compound library Ingredien Molecule Caco- Mol ID MW AlogP OB (%) BBB DL FASA- HL t Name Name 2 shengdi MOL012254 campesterol 400.8 7.63 37.58 1.34 0.98 0.7 0.21 20.2 shengdi MOL000519 coniferin 314.4 3.16 31.11 0.42 -0.2 0.3 0.27 74.6 beta- shengdi MOL000359 414.8 8.08 36.91 1.32 0.99 0.8 0.23 20.2 sitosterol pachymic shengdi MOL000289 528.9 6.54 33.63 0.1 -0.6 0.8 0 9.27 acid Poricoic acid shengdi MOL000291 484.7 5.64 30.52 -0.08 -0.9 0.8 0 8.67 B Chrysanthem shengdi MOL004492 585 8.24 38.72 0.51 -1 0.6 0.3 17.5 axanthin 20- shengdi MOL011455 Hexadecano 418.6 1.91 32.7 -0.24 -0.4 0.7 0.29 104 ylingenol huanglian MOL001454 berberine 336.4 3.45 36.86 1.24 0.57 0.8 0.19 6.57 huanglian MOL013352 Obacunone 454.6 2.68 43.29 0.01 -0.4 0.8 0.31 -13 huanglian MOL002894 berberrubine 322.4 3.2 35.74 1.07 0.17 0.7 0.24 6.46 huanglian MOL002897 epiberberine 336.4 3.45 43.09 1.17 0.4 0.8 0.19 6.1 huanglian MOL002903 (R)-Canadine 339.4 3.4 55.37 1.04 0.57 0.8 0.2 6.41 huanglian MOL002904 Berlambine 351.4 2.49 36.68 0.97 0.17 0.8 0.28 7.33 Corchorosid huanglian MOL002907 404.6 1.34 105 -0.91 -1.3 0.8 0.29 6.68 e A_qt Magnogrand huanglian MOL000622 266.4 1.18 63.71 0.02 -0.2 0.2 0.3 3.17 iolide huanglian MOL000762 Palmidin A 510.5 4.52 35.36 -0.38 -1.5 0.7 0.39 33.2 huanglian MOL000785 palmatine 352.4 3.65 64.6 1.33 0.37 0.7 0.13 2.25 huanglian MOL000098 quercetin 302.3 1.5 46.43 0.05 -0.8 0.3 0.38 14.4 huanglian MOL001458 coptisine 320.3 3.25 30.67 1.21 0.32 0.9 0.26 9.33 huanglian MOL002668 Worenine -
Coding RNA Genes
Review A guide to naming human non-coding RNA genes Ruth L Seal1,2,* , Ling-Ling Chen3, Sam Griffiths-Jones4, Todd M Lowe5, Michael B Mathews6, Dawn O’Reilly7, Andrew J Pierce8, Peter F Stadler9,10,11,12,13, Igor Ulitsky14 , Sandra L Wolin15 & Elspeth A Bruford1,2 Abstract working on non-coding RNA (ncRNA) nomenclature in the mid- 1980s with the approval of initial gene symbols for mitochondrial Research on non-coding RNA (ncRNA) is a rapidly expanding field. transfer RNA (tRNA) genes. Since then, we have worked closely Providing an official gene symbol and name to ncRNA genes brings with experts in the ncRNA field to develop symbols for many dif- order to otherwise potential chaos as it allows unambiguous ferent kinds of ncRNA genes. communication about each gene. The HUGO Gene Nomenclature The number of genes that the HGNC has named per ncRNA class Committee (HGNC, www.genenames.org) is the only group with is shown in Fig 1, and ranges in number from over 4,500 long the authority to approve symbols for human genes. The HGNC ncRNA (lncRNA) genes and over 1,900 microRNA genes, to just four works with specialist advisors for different classes of ncRNA to genes in the vault and Y RNA classes. Every gene symbol has a ensure that ncRNA nomenclature is accurate and informative, Symbol Report on our website, www.genenames.org, which where possible. Here, we review each major class of ncRNA that is displays the gene symbol, gene name, chromosomal location and currently annotated in the human genome and describe how each also includes links to key resources such as Ensembl (Zerbino et al, class is assigned a standardised nomenclature. -
Long Non-Coding RNA Lncshgl Recruits Hnrnpa1 to Suppress Hepatic Gluconeogenesis and Lipogenesis
Page 1 of 60 Diabetes Long non-coding RNA LncSHGL recruits hnRNPA1 to suppress hepatic gluconeogenesis and lipogenesis Junpei Wang1,2#, Weili Yang1,2#, Zhenzhen Chen1, Ji Chen1, Yuhong Meng1, Biaoqi Feng1, Libo Sun3, Lin Dou4, Jian Li4, Qinghua Cui2*, Jichun Yang1* 1Department of Physiology and Pathophysiology, School of Basic Medical Sciences Key Laboratory of Molecular Cardiovascular Sciences of the Ministry of Education Center for Non-coding RNA Medicine Peking University Health Science Center Beijing 100191, China 2Department of Biomedical Informatics, School of Basic Medical Sciences Key Laboratory of Molecular Cardiovascular Sciences of the Ministry of Education, Center for Non-coding RNA Medicine Peking University Health Science Center, Beijing 100191, China 3Beijing You An Hospital,Capital Medical University, Beijing 100069, China 4Key Laboratory of Geriatrics, Beijing Institute of Geriatrics & Beijing Hospital, Ministry of Health, Beijing 100730, China #These authors contributed equally to this work *Correspondence to: Jichun Yang, Ph.D. Department of Physiology and Pathophysiology, School of Basic Medical Sciences Peking University Health Science Center, Beijing 100191, China Email: [email protected]; Tel: (+86) 10-82801403 Or to: Qinghua Cui, Ph.D. Department of Biomedical Informatics, School of Basic Medical Sciences Peking University Health Science Center, Beijing 100191, China Email:[email protected]; Tel:(+86)10-82801585 1 Diabetes Publish Ahead of Print, published online January 30, 2018 Diabetes Page 2 of 60 Abstract Mammalian genomes encode a huge number of LncRNAs with unknown functions. This study determined the role and mechanism of a new LncRNA, LncRNA Suppressor of Hepatic Gluconeogenesis and Lipogenesis (LncSHGL), in regulating hepatic glucose/lipid metabolism. -
NSUN2 As the Methyltransferase and ALYREF As an M5c Reader
Cell Research (2017) 27:606-625. ORIGINAL ARTICLE www.nature.com/cr 5-methylcytosine promotes mRNA export — NSUN2 as the methyltransferase and ALYREF as an m5C reader Xin Yang1, 2, 3, *, Ying Yang2, *, Bao-Fa Sun2, *, Yu-Sheng Chen2, 3, *, Jia-Wei Xu1, 2, *, Wei-Yi Lai3, 4, *, Ang Li2, 3, Xing Wang2, 5, Devi Prasad Bhattarai2, 3, Wen Xiao2, Hui-Ying Sun2, Qin Zhu2, 3, Hai-Li Ma2, 3, Samir Adhikari2, Min Sun2, Ya-Juan Hao2, Bing Zhang2, Chun-Min Huang2, Niu Huang6, Gui-Bin Jiang4, Yong-Liang Zhao2, Hai-Lin Wang4, Ying-Pu Sun1, Yun-Gui Yang2, 3 1Center for Reproductive Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450000, China; 2Key Laboratory of Genomic and Precision Medicine, Collaborative Innovation Center of Genetics and Development, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China; 3School of Life Science, University of Chinese Academy of Sciences, Beijing 100049, China; 4State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; 5Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China; 6National Institute of Biological Sciences, Beijing 102206, China 5-methylcytosine (m5C) is a post-transcriptional RNA modification identified in both stable and highly abundant tRNAs and rRNAs, and in mRNAs. However, its regulatory role in mRNA metabolism is still largely unknown. Here, we reveal that m5C modification is enriched in CG-rich regions and in regions immediately downstream of trans- lation initiation sites and has conserved, tissue-specific and dynamic features across mammalian transcriptomes. -
MOCHI Enables Discovery of Heterogeneous Interactome Modules in 3D Nucleome
Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press MOCHI enables discovery of heterogeneous interactome modules in 3D nucleome Dechao Tian1,# , Ruochi Zhang1,# , Yang Zhang1, Xiaopeng Zhu1, and Jian Ma1,* 1Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA #These two authors contributed equally *Correspondence: [email protected] Contact To whom correspondence should be addressed: Jian Ma School of Computer Science Carnegie Mellon University 7705 Gates-Hillman Complex 5000 Forbes Avenue Pittsburgh, PA 15213 Phone: +1 (412) 268-2776 Email: [email protected] 1 Downloaded from genome.cshlp.org on October 4, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract The composition of the cell nucleus is highly heterogeneous, with different constituents forming complex interactomes. However, the global patterns of these interwoven heterogeneous interactomes remain poorly understood. Here we focus on two different interactomes, chromatin interaction network and gene regulatory network, as a proof-of-principle, to identify heterogeneous interactome modules (HIMs), each of which represents a cluster of gene loci that are in spatial contact more frequently than expected and that are regulated by the same group of transcription factors. HIM integrates transcription factor binding and 3D genome structure to reflect “transcriptional niche” in the nucleus. We develop a new algorithm MOCHI to facilitate the discovery of HIMs based on network motif clustering in heterogeneous interactomes. By applying MOCHI to five different cell types, we found that HIMs have strong spatial preference within the nucleus and exhibit distinct functional properties. Through integrative analysis, this work demonstrates the utility of MOCHI to identify HIMs, which may provide new perspectives on the interplay between transcriptional regulation and 3D genome organization. -
Pathogenic Variants in Glutamyl-Trnagln Amidotransferase Subunits Cause a Lethal Mitochondrial Cardiomyopathy Disorder
ARTICLE DOI: 10.1038/s41467-018-06250-w OPEN Pathogenic variants in glutamyl-tRNAGln amidotransferase subunits cause a lethal mitochondrial cardiomyopathy disorder Marisa W. Friederich1, Sharita Timal2,3, Christopher A. Powell4, Cristina Dallabona5, Alina Kurolap6,7, Sara Palacios-Zambrano et al.# 1234567890():,; Mitochondrial protein synthesis requires charging mt-tRNAs with their cognate amino acids by mitochondrial aminoacyl-tRNA synthetases, with the exception of glutaminyl mt-tRNA (mt-tRNAGln). mt-tRNAGln is indirectly charged by a transamidation reaction involving the GatCAB aminoacyl-tRNA amidotransferase complex. Defects involving the mitochondrial protein synthesis machinery cause a broad spectrum of disorders, with often fatal outcome. Here, we describe nine patients from five families with genetic defects in a GatCAB complex subunit, including QRSL1, GATB, and GATC, each showing a lethal metabolic cardiomyopathy syndrome. Functional studies reveal combined respiratory chain enzyme deficiencies and mitochondrial dysfunction. Aminoacylation of mt-tRNAGln and mitochondrial protein trans- lation are deficient in patients’ fibroblasts cultured in the absence of glutamine but restore in high glutamine. Lentiviral rescue experiments and modeling in S. cerevisiae homologs confirm pathogenicity. Our study completes a decade of investigations on mitochondrial aminoacy- lation disorders, starting with DARS2 and ending with the GatCAB complex. Correspondence and requests for materials should be addressed to J.L.K.V.H. (email: [email protected]). #A full list of authors and their affliations appears at the end of the paper. NATURE COMMUNICATIONS | (2018) 9:4065 | DOI: 10.1038/s41467-018-06250-w | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | DOI: 10.1038/s41467-018-06250-w itochondrial disorders are highly heterogeneous due to pericardial effusion.