Literature DB >> 10657981

The balance sheet for transcription: an analysis of nuclear RNA metabolism in mammalian cells.

D A Jackson1, A Pombo, F Iborra.   

Abstract

The control of RNA synthesis from protein-coding genes is fundamental in determining the various cell types of higher eukaryotes. The activation of these genes is driven by promoter complexes, and RNA synthesis is performed by an enzyme mega-complex-the RNA polymerase II holoenzyme. These two complexes are the fundamental components required to initiate gene expression and generate the primary transcripts that, after processing, yield mRNAs that pass to the cytoplasm where protein synthesis occurs. But although this gene expression pathway has been studied intensively, aspects of RNA metabolism remain difficult to comprehend. In particular, it is unclear why >95% of RNA polymerized by polymerase II remains in the nucleus, where it is recycled. To explain this apparent paradox, this review presents a detailed description of nuclear RNA (nRNA) metabolism in mammalian cells. We evaluate the number of active transcription units, discuss the distribution of polymerases on active genes, and assess the efficiency with which the products mature and pass to the cytoplasm. Differences between the behavior of mRNAs on this productive pathway and primary transcripts that never leave the nucleus lead us to propose that these represent distinct populations. We discuss possible roles for nonproductive RNAs and present a model to describe the metabolism of these RNAs in the nuclei of mammalian cells.-Jackson, D. A., Pombo, A., Iborra, F. The balance sheet for transcription: an analysis of nuclear RNA metabolism in mammalian cells.

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Year:  2000        PMID: 10657981

Source DB:  PubMed          Journal:  FASEB J        ISSN: 0892-6638            Impact factor:   5.191


  58 in total

Review 1.  Functional architecture in the cell nucleus.

Authors:  M Dundr; T Misteli
Journal:  Biochem J       Date:  2001-06-01       Impact factor: 3.857

2.  General statistics of stochastic process of gene expression in eukaryotic cells.

Authors:  V A Kuznetsov; G D Knott; R F Bonner
Journal:  Genetics       Date:  2002-07       Impact factor: 4.562

3.  Disclosing hidden transcripts: mouse natural sense-antisense transcripts tend to be poly(A) negative and nuclear localized.

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Journal:  Genome Res       Date:  2005-03-21       Impact factor: 9.043

4.  A model for intracellular trafficking of adenoviral vectors.

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Journal:  Biophys J       Date:  2005-06-24       Impact factor: 4.033

5.  A conserved organization of transcription during embryonic stem cell differentiation and in cells with high C value.

Authors:  Inês Faro-Trindade; Peter R Cook
Journal:  Mol Biol Cell       Date:  2006-04-19       Impact factor: 4.138

Review 6.  Transcription factories: gene expression in unions?

Authors:  Heidi Sutherland; Wendy A Bickmore
Journal:  Nat Rev Genet       Date:  2009-07       Impact factor: 53.242

7.  Genome-wide detection and analysis of hippocampus core promoters using DeepCAGE.

Authors:  Eivind Valen; Giovanni Pascarella; Alistair Chalk; Norihiro Maeda; Miki Kojima; Chika Kawazu; Mitsuyoshi Murata; Hiromi Nishiyori; Dejan Lazarevic; Dario Motti; Troels Torben Marstrand; Man-Hung Eric Tang; Xiaobei Zhao; Anders Krogh; Ole Winther; Takahiro Arakawa; Jun Kawai; Christine Wells; Carsten Daub; Matthias Harbers; Yoshihide Hayashizaki; Stefano Gustincich; Albin Sandelin; Piero Carninci
Journal:  Genome Res       Date:  2008-12-11       Impact factor: 9.043

8.  Spatial organization of RNA polymerase II inside a mammalian cell nucleus revealed by reflected light-sheet superresolution microscopy.

Authors:  Ziqing W Zhao; Rahul Roy; J Christof M Gebhardt; David M Suter; Alec R Chapman; X Sunney Xie
Journal:  Proc Natl Acad Sci U S A       Date:  2013-12-30       Impact factor: 11.205

9.  Physical principles for scalable neural recording.

Authors:  Adam H Marblestone; Bradley M Zamft; Yael G Maguire; Mikhail G Shapiro; Thaddeus R Cybulski; Joshua I Glaser; Dario Amodei; P Benjamin Stranges; Reza Kalhor; David A Dalrymple; Dongjin Seo; Elad Alon; Michel M Maharbiz; Jose M Carmena; Jan M Rabaey; Edward S Boyden; George M Church; Konrad P Kording
Journal:  Front Comput Neurosci       Date:  2013-10-21       Impact factor: 2.380

10.  Microarray analysis of cytoplasmic versus whole cell RNA reveals a considerable number of missed and false positive mRNAs.

Authors:  Heidi W Trask; Richard Cowper-Sal-lari; Maureen A Sartor; Jiang Gui; Catherine V Heath; Janhavi Renuka; Azara-Jane Higgins; Peter Andrews; Murray Korc; Jason H Moore; Craig R Tomlinson
Journal:  RNA       Date:  2009-08-24       Impact factor: 4.942

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