Long Non-Coding RNA EGOT Promotes the Malignant Phenotypes of Hepatocellular Carcinoma Cells and Increases the Expression of HMGA2 Via Down-Regulating Mir-33A-5P
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Mrna-Lncrna Co-Expression Network Analysis Reveals the Role of Lncrnas in Immune Dysfunction During Severe SARS-Cov-2 Infection
viruses Article mRNA-lncRNA Co-Expression Network Analysis Reveals the Role of lncRNAs in Immune Dysfunction during Severe SARS-CoV-2 Infection Sumit Mukherjee 1 , Bodhisattwa Banerjee 2 , David Karasik 2 and Milana Frenkel-Morgenstern 1,* 1 Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel; [email protected] 2 Musculoskeletal Genetics Laboratory, Azrieli Faculty of Medicine, Bar-Ilan University, Safed 1311502, Israel; [email protected] (B.B.); [email protected] (D.K.) * Correspondence: [email protected]; Tel.: +972-72-264-4901 Abstract: The recently emerged SARS-CoV-2 virus is responsible for the ongoing COVID-19 pan- demic that has rapidly developed into a global public health threat. Patients severely affected with COVID-19 present distinct clinical features, including acute respiratory disorder, neutrophilia, cy- tokine storm, and sepsis. In addition, multiple pro-inflammatory cytokines are found in the plasma of such patients. Transcriptome sequencing of different specimens obtained from patients suffering from severe episodes of COVID-19 shows dynamics in terms of their immune responses. However, those host factors required for SARS-CoV-2 propagation and the underlying molecular mechanisms responsible for dysfunctional immune responses during COVID-19 infection remain elusive. In the present study, we analyzed the mRNA-long non-coding RNA (lncRNA) co-expression network derived from publicly available SARS-CoV-2-infected transcriptome data of human lung epithelial Citation: Mukherjee, S.; Banerjee, B.; cell lines and bronchoalveolar lavage fluid (BALF) from COVID-19 patients. Through co-expression Karasik, D.; Frenkel-Morgenstern, M. -
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. -
Whole Exome Sequencing in Families at High Risk for Hodgkin Lymphoma: Identification of a Predisposing Mutation in the KDR Gene
Hodgkin Lymphoma SUPPLEMENTARY APPENDIX Whole exome sequencing in families at high risk for Hodgkin lymphoma: identification of a predisposing mutation in the KDR gene Melissa Rotunno, 1 Mary L. McMaster, 1 Joseph Boland, 2 Sara Bass, 2 Xijun Zhang, 2 Laurie Burdett, 2 Belynda Hicks, 2 Sarangan Ravichandran, 3 Brian T. Luke, 3 Meredith Yeager, 2 Laura Fontaine, 4 Paula L. Hyland, 1 Alisa M. Goldstein, 1 NCI DCEG Cancer Sequencing Working Group, NCI DCEG Cancer Genomics Research Laboratory, Stephen J. Chanock, 5 Neil E. Caporaso, 1 Margaret A. Tucker, 6 and Lynn R. Goldin 1 1Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 2Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; 3Ad - vanced Biomedical Computing Center, Leidos Biomedical Research Inc.; Frederick National Laboratory for Cancer Research, Frederick, MD; 4Westat, Inc., Rockville MD; 5Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD; and 6Human Genetics Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA ©2016 Ferrata Storti Foundation. This is an open-access paper. doi:10.3324/haematol.2015.135475 Received: August 19, 2015. Accepted: January 7, 2016. Pre-published: June 13, 2016. Correspondence: [email protected] Supplemental Author Information: NCI DCEG Cancer Sequencing Working Group: Mark H. Greene, Allan Hildesheim, Nan Hu, Maria Theresa Landi, Jennifer Loud, Phuong Mai, Lisa Mirabello, Lindsay Morton, Dilys Parry, Anand Pathak, Douglas R. Stewart, Philip R. Taylor, Geoffrey S. Tobias, Xiaohong R. Yang, Guoqin Yu NCI DCEG Cancer Genomics Research Laboratory: Salma Chowdhury, Michael Cullen, Casey Dagnall, Herbert Higson, Amy A. -
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. -
Hippo and Sonic Hedgehog Signalling Pathway Modulation of Human Urothelial Tissue Homeostasis
Hippo and Sonic Hedgehog signalling pathway modulation of human urothelial tissue homeostasis Thomas Crighton PhD University of York Department of Biology November 2020 Abstract The urinary tract is lined by a barrier-forming, mitotically-quiescent urothelium, which retains the ability to regenerate following injury. Regulation of tissue homeostasis by Hippo and Sonic Hedgehog signalling has previously been implicated in various mammalian epithelia, but limited evidence exists as to their role in adult human urothelial physiology. Focussing on the Hippo pathway, the aims of this thesis were to characterise expression of said pathways in urothelium, determine what role the pathways have in regulating urothelial phenotype, and investigate whether the pathways are implicated in muscle-invasive bladder cancer (MIBC). These aims were assessed using a cell culture paradigm of Normal Human Urothelial (NHU) cells that can be manipulated in vitro to represent different differentiated phenotypes, alongside MIBC cell lines and The Cancer Genome Atlas resource. Transcriptomic analysis of NHU cells identified a significant induction of VGLL1, a poorly understood regulator of Hippo signalling, in differentiated cells. Activation of upstream transcription factors PPARγ and GATA3 and/or blockade of active EGFR/RAS/RAF/MEK/ERK signalling were identified as mechanisms which induce VGLL1 expression in NHU cells. Ectopic overexpression of VGLL1 in undifferentiated NHU cells and MIBC cell line T24 resulted in significantly reduced proliferation. Conversely, knockdown of VGLL1 in differentiated NHU cells significantly reduced barrier tightness in an unwounded state, while inhibiting regeneration and increasing cell cycle activation in scratch-wounded cultures. A signalling pathway previously observed to be inhibited by VGLL1 function, YAP/TAZ, was unaffected by VGLL1 manipulation. -
Gene Expression Signature of Menstrual Cyclic Phase in Normal Cycling Endometrium
Gene Expression Signature of Menstrual Cyclic Phase in Normal Cycling Endometrium A Thesis SUBMITTED TO THE FACULTY OF UNIVERSITY OF MINNESOTA BY Ling Cen IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE Adviser: George Vasmatzis Co-Adviser: Claudia Neuhauser December 2014 © Ling Cen 2014 Acknowledgements First, I would like to thank my advisor, Dr. George Vasmatzis for giving me an opportunity to work on this project in his group. This work could not have been completed without his kind guidance. I also would like to thank my co-advisor, Dr. Claudia Neuhauser for her advising and guidance during the study in the program. Further, I also very much appreciate Dr. Peter Li for serving on my committee and for his helpful discussions. Additionally, I’m grateful to Dr. Y.F. Wong for his generosity in sharing the gene expression data for our analysis. Most importantly, I am deeply indebted to my family and friends, for their continuous love, support, patience, and encouragement during the completion of this work. i Abstract Gene expression profiling has been widely used in understanding global gene expression alterations in endometrial cancer vs. normal cells. In many microarray-based endometrial cancer studies, comparisons of cancer with normal cells were generally made using heterogeneous samples in terms of menstrual cycle phases, or status of hormonal therapies, etc, which may confound the search for differentially expressed genes playing roles in the progression of endometrial cancer. These studies will consequently fail to uncover genes that are important in endometrial cancer biology. Thus it is fundamentally important to identify a gene signature for discriminating normal endometrial cyclic phases. -
Long Noncoding RNA Eosinophil Granule Ontogeny Transcript Inhibits Cell Proliferation and Migration and Promotes Cell Apoptosis in Human Glioma
EXPERIMENTAL AND THERAPEUTIC MEDICINE 14: 3817-3823, 2017 Long noncoding RNA eosinophil granule ontogeny transcript inhibits cell proliferation and migration and promotes cell apoptosis in human glioma YOU WU1*, SHUNLI LIANG1*, BIN XU1, RONGBO ZHANG1, MINZI ZHU1, WEIYING ZHOU1, SHUIJING ZHANG1, JINHUI GUO1, LINSHENG XU1 and HONGYE ZHU2 Departments of 1Neurology and 2Oncology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310005, P.R. China Received August 25, 2016; Accepted May 15, 2017 DOI: 10.3892/etm.2017.4949 Abstract. Glioma is the most common primary brain tumor Introduction and represents one of the most aggressive and lethal types of human cancer. Recent advances have implicated long Glioma is the most common brain tumor, accounting for noncoding RNAs (lncRNAs) as crucial mediators of cancer >50% of all brain tumors (1). According to a population-based development and progression. The present study aimed to investigation, the overall median survival duration for patients investigate the role of a newly-discovered lncRNA, termed with malignant glioma is ~15 months (2). Despite significant eosinophil granule ontogeny transcript (EGOT), in the advances in the therapeutic strategies of glioma, including aggressive abilities of cells in human glioma. It was initially neurosurgical approaches, chemotherapy and radiotherapy, found that the relative transcription level of EGOT in glioma the prognosis of patients with malignant glioma remains cancerous tissues was significantly lower than that in adjacent poor, primarily due to the fact that malignant glioma cells non-cancerous tissues. EGOT was differentially expressed in a are highly aggressive and capable of infiltrating into adjacent series of glioma cell lines, with its lowest level in high aggres- normal brain tissue, leading to the eventual failure of complete sive U251 and U87 cells. -
2014-Platform-Abstracts.Pdf
American Society of Human Genetics 64th Annual Meeting October 18–22, 2014 San Diego, CA PLATFORM ABSTRACTS Abstract Abstract Numbers Numbers Saturday 41 Statistical Methods for Population 5:30pm–6:50pm: Session 2: Plenary Abstracts Based Studies Room 20A #198–#205 Featured Presentation I (4 abstracts) Hall B1 #1–#4 42 Genome Variation and its Impact on Autism and Brain Development Room 20BC #206–#213 Sunday 43 ELSI Issues in Genetics Room 20D #214–#221 1:30pm–3:30pm: Concurrent Platform Session A (12–21): 44 Prenatal, Perinatal, and Reproductive 12 Patterns and Determinants of Genetic Genetics Room 28 #222–#229 Variation: Recombination, Mutation, 45 Advances in Defining the Molecular and Selection Hall B1 Mechanisms of Mendelian Disorders Room 29 #230–#237 #5-#12 13 Genomic Studies of Autism Room 6AB #13–#20 46 Epigenomics of Normal Populations 14 Statistical Methods for Pedigree- and Disease States Room 30 #238–#245 Based Studies Room 6CF #21–#28 15 Prostate Cancer: Expression Tuesday Informing Risk Room 6DE #29–#36 8:00pm–8:25am: 16 Variant Calling: What Makes the 47 Plenary Abstracts Featured Difference? Room 20A #37–#44 Presentation III Hall BI #246 17 New Genes, Incidental Findings and 10:30am–12:30pm:Concurrent Platform Session D (49 – 58): Unexpected Observations Revealed 49 Detailing the Parts List Using by Exome Sequencing Room 20BC #45–#52 Genomic Studies Hall B1 #247–#254 18 Type 2 Diabetes Genetics Room 20D #53–#60 50 Statistical Methods for Multigene, 19 Genomic Methods in Clinical Practice Room 28 #61–#68 Gene Interaction -
Genetic and Genomics Laboratory Tools and Approaches
Genetic and Genomics Laboratory Tools and Approaches Meredith Yeager, PhD Cancer Genomics Research Laboratory Division of Cancer Epidemiology and Genetics [email protected] DCEG Radiation Epidemiology and Dosimetry Course 2019 www.dceg.cancer.gov/RadEpiCourse (Recent) history of genetics 2 Sequencing of the Human Genome Science 291, 1304-1351 (2001) 3 The Human Genome – 2019 • ~3.3 billion bases (A, C, G, T) • ~20,000 protein-coding genes, many non-coding RNAs (~2% of the genome) • Annotation ongoing – the initial sequencing in 2001 is still being refined, assembled and annotated, even now – hg38 • Variation (polymorphism) present within humans – Population-specific – Cosmopolitan 4 Types of polymorphisms . Single nucleotide polymorphisms (SNPs) . Common SNPs are defined as > 5% in at least one population . Abundant in genome (~50 million and counting) ATGGAACGA(G/C)AGGATA(T/A)TACGCACTATGAAG(C/A)CGGTGAGAGG . Repeats of DNA (long, short, complex, simple), insertions/deletions . A small fraction of SNPs and other types of variation are very or slightly deleterious and may contribute by themselves or with other genetic or environmental factors to a phenotype or disease 5 Different mutation rates at the nucleotide level Mutation type Mutation rate (per generation) Transition on a CpG 1.6X10-7 Transversion on a CpG 4.4X10-8 Transition: purine to purine Transition out of CpG 1.2X10-8 Transversion: purine to pyrimidine Transversion out of CpG 5.5X10-9 Substitution (average) 2.3X10-8 A and G are purines Insertion/deletion (average) 2.3X10-9 C and T are pyrimidines Mutation rate (average) 2.4X10-8 . Size of haploid genome : 3.3X109 nucleotides . -
Download Special Issue
International Journal of Genomics Noncoding RNAs in Health and Disease Lead Guest Editor: Michele Purrello Guest Editors: Massimo Romani and Davide Barbagallo Noncoding RNAs in Health and Disease International Journal of Genomics Noncoding RNAs in Health and Disease Lead Guest Editor: Michele Purrello Guest Editors: Massimo Romani and Davide Barbagallo Copyright © 2018 Hindawi. All rights reserved. This is a special issue published in “International Journal of Genomics.” All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Editorial Board Andrea C. Belin, Sweden M. Hadzopoulou-Cladaras, Greece Ferenc Olasz, Hungary Jacques Camonis, France Sylvia Hagemann, Austria Elena Pasyukova, Russia Prabhakara V. Choudary, USA Henry Heng, USA Graziano Pesole, Italy Martine A. Collart, Switzerland Eivind Hovig, Norway Giulia Piaggio, Italy Monika Dmitrzak-Weglarz, Poland Hieronim Jakubowski, USA Mohamed Salem, USA Marco Gerdol, Italy B.-H. Jeong, Republic of Korea Wilfred van IJcken, Netherlands João Paulo Gomes, Portugal Atsushi Kurabayashi, Japan Brian Wigdahl, USA Soraya E. Gutierrez, Chile Giuliana Napolitano, Italy Jinfa Zhang, USA Contents Noncoding RNAs in Health and Disease Davide Barbagallo, Gaetano Vittone, Massimo Romani , and Michele Purrello Volume 2018, Article ID 9135073, 2 pages Circular RNAs: Biogenesis, Function, and a Role as Possible Cancer Biomarkers Luka Bolha, -
Identification of Lncrna EGOT As a Tumor Suppressor in Renal Cell Carcinoma
7072 MOLECULAR MEDICINE REPORTS 16: 7072-7079, 2017 Identification of lncRNA EGOT as a tumor suppressor in renal cell carcinoma LU JIN1-3, JING QUAN1-3, XIANG PAN1-3, TAO HE1,3, JIA HU1,3, YIFAN LI1,3, YAOTING GUI2,3, SHANGQI YANG1, XIANGMING MAO1, YUN CHEN4 and YONGQING LAI1,3 1Department of Urology, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036; 2Department of Urology, Anhui Medical University, Hefei, Anhui 230032; 3The Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics; 4Department of Ultrasound, Peking University Shenzhen Hospital, Shenzhen, Guangdong 518036, P.R. China Received July 22, 2016; Accepted July 13, 2017 DOI: 10.3892/mmr.2017.7470 Abstract. Renal cell carcinoma (RCC) is the most common The prognosis of patients with RCC remains unfavorable, type of kidney cancer and the prognosis of metastatic RCC particularly for those with advanced tumors (6). It is essential remains poor, with a high rate of recurrence and mortality. to diagnose RCC as early as possible and to identify novel Long non-coding RNA (lncRNA) is a class of RNA which biomarkers for RCC. serves important roles in multiple cellular processes and Long non-coding RNAs (lncRNAs) are a group of tumorigenesis. In the present study, the expression and non-protein coding transcripts that have a length of >200 nucle- function of lncRNA eosinophil granule ontogeny transcript otides (7,8). lncRNAs were regarded as ‘transcriptional noise’ (EGOT) were examined in RCC. In 24 paired tissues (RCC when identified initially. However, accumulating evidence has tissues and adjacent normal tissues) the results of reverse demonstrated that lncRNAs may influence gene expression transcription-quantitative polymerase chain reaction analysis via transcriptional, post-transcriptional or epigenetic regula- revealed that EGOT was downregulated in 22 RCC tissues tion (9). -
Original File Was Test.Tex
Molecular Evolution of the non-coding Eosinophil Granule Ontogeny Transcript EGOT Dominic Rose1,C, Peter F. Stadler2,3,4,5,6,7 1) Bioinformatics Group, Department of Computer Science, University of Freiburg, Georges-Köhler-Allee 106, D-79110 Freiburg, Germany. 2) Bioinformatics Group, Department of Computer Science, and Interdisciplinary Center for Bioinformatics, University of Leipzig, Härtelstr. 16-18, D-04107 Leipzig, Germany. 3) Max Planck Institute for Mathematics in the Sciences, Inselstr. 22, D-04103 Leipzig, Germany. 4) Fraunhofer Institut für Zelltherapie und Immunologie - IZI Perlickstr. 1, D-04103 Leipzig, Germany. 5) Department of Theoretical Chemistry, University of Vienna, Währingerstr. 17, A-1090 Wien, Austria. 6) Center for non-coding RNA in Technology and Health, University of Copenhagen, Grønnegardsvej 3, DK-1870 Frederiksberg C, Denmark. 7) Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM 87501, USA. C) Corresponding author: [email protected] Abstract Eukaryotic genomes are pervasively transcribed. A large fraction of the transcriptional output consists of long, mRNA-like, non-protein-coding transcripts (mlncRNAs). The evolutionary history of mlncRNAs is still largely uncharted territory. In this contribution, we explore in detail the evolutionary traces of the eosinophil granule ontogeny transcript (EGOT), an experimentally confirmed representative of an abundant class of totally intronic non-coding transcripts (TINs). EGOT is located antisense to an intron of the ITPR1 gene. We computationally identify putative EGOT orthologs in the genomes of 32 different amniotes, including orthologs from primates, rodents, ungulates, carnivores, afrotherians, and xenarthrans, as well as putative candidates from basal amniotes, such as opossum or platypus. We investigate the EGOT gene phylogeny, analyse patterns of sequence conservation, and the evolutionary conservation of the EGOT gene structure.