Literature DB >> 19823741

Metabolic tagging and purification of nascent RNA: implications for transcriptomics.

Caroline C Friedel1, Lars Dölken.   

Abstract

Gene expression profiling to analyze cellular responses against different stimuli or conditions is generally performed at the total cellular RNA level. This results in poor resolution of the temporal kinetics of the cellular response and a bias towards detecting up-regulation of short-lived transcripts. Furthermore, changes in transcription rate and RNA stability cannot be distinguished. These problems can be addressed by analyzing nascent RNA instead of total cellular RNA. Throughout the last few years methods have been developed for metabolic tagging and purification of nascent RNA. In this article, we review these experimental procedures and discuss their implications for large-scale gene expression profiling.

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Year:  2009        PMID: 19823741     DOI: 10.1039/b911233b

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  25 in total

Review 1.  RNA-biology ruling cancer progression? Focus on 3'UTRs and splicing.

Authors:  Ayse Elif Erson-Bensan
Journal:  Cancer Metastasis Rev       Date:  2020-09       Impact factor: 9.264

2.  Transcript dynamics of proinflammatory genes revealed by sequence analysis of subcellular RNA fractions.

Authors:  Dev M Bhatt; Amy Pandya-Jones; Ann-Jay Tong; Iros Barozzi; Michelle M Lissner; Gioacchino Natoli; Douglas L Black; Stephen T Smale
Journal:  Cell       Date:  2012-07-20       Impact factor: 41.582

3.  Metabolic labeling and recovery of nascent RNA to accurately quantify mRNA stability.

Authors:  Joseph Russo; Adam M Heck; Jeffrey Wilusz; Carol J Wilusz
Journal:  Methods       Date:  2017-02-20       Impact factor: 3.608

Review 4.  Genome-wide technology for determining RNA stability in mammalian cells: historical perspective and recent advantages based on modified nucleotide labeling.

Authors:  Hidenori Tani; Nobuyoshi Akimitsu
Journal:  RNA Biol       Date:  2012-10-01       Impact factor: 4.652

5.  Mouse TU tagging: a chemical/genetic intersectional method for purifying cell type-specific nascent RNA.

Authors:  Leslie Gay; Michael R Miller; P Britten Ventura; Vidusha Devasthali; Zer Vue; Heather L Thompson; Sally Temple; Hui Zong; Michael D Cleary; Kryn Stankunas; Chris Q Doe
Journal:  Genes Dev       Date:  2013-01-01       Impact factor: 11.361

6.  Applying thiouracil tagging to mouse transcriptome analysis.

Authors:  Leslie Gay; Kate V Karfilis; Michael R Miller; Chris Q Doe; Kryn Stankunas
Journal:  Nat Protoc       Date:  2014-01-23       Impact factor: 13.491

7.  Metabolic labeling of newly transcribed RNA for high resolution gene expression profiling of RNA synthesis, processing and decay in cell culture.

Authors:  Bernd Rädle; Andrzej J Rutkowski; Zsolt Ruzsics; Caroline C Friedel; Ulrich H Koszinowski; Lars Dölken
Journal:  J Vis Exp       Date:  2013-08-08       Impact factor: 1.355

8.  A comparison of metabolic labeling and statistical methods to infer genome-wide dynamics of RNA turnover.

Authors:  Etienne Boileau; Janine Altmüller; Isabel S Naarmann-de Vries; Christoph Dieterich
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

9.  4-thiouridine inhibits rRNA synthesis and causes a nucleolar stress response.

Authors:  Kaspar Burger; Bastian Mühl; Markus Kellner; Michaela Rohrmoser; Anita Gruber-Eber; Lukas Windhager; Caroline C Friedel; Lars Dölken; Dirk Eick
Journal:  RNA Biol       Date:  2013-09-04       Impact factor: 4.652

10.  Real-time transcriptional profiling of cellular and viral gene expression during lytic cytomegalovirus infection.

Authors:  Lisa Marcinowski; Michael Lidschreiber; Lukas Windhager; Martina Rieder; Jens B Bosse; Bernd Rädle; Thomas Bonfert; Ildiko Györy; Miranda de Graaf; Olivia Prazeres da Costa; Philip Rosenstiel; Caroline C Friedel; Ralf Zimmer; Zsolt Ruzsics; Lars Dölken
Journal:  PLoS Pathog       Date:  2012-09-06       Impact factor: 6.823

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