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Post-Transcriptional Gene Regulation

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Cover of 'Post-Transcriptional Gene Regulation'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction to Bioinformatics Resources for Post-transcriptional Regulation of Gene Expression.
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    Chapter 2 Post-Transcriptional Gene Regulation
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    Chapter 3 Transcriptional Regulation with CRISPR/Cas9 Effectors in Mammalian Cells.
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    Chapter 4 Studying the Translatome with Polysome Profiling.
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    Chapter 5 Exploring Ribosome Positioning on Translating Transcripts with Ribosome Profiling.
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    Chapter 6 Post-Transcriptional Gene Regulation
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    Chapter 7 Use of the pBUTR Reporter System for Scalable Analysis of 3' UTR-Mediated Gene Regulation.
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    Chapter 8 Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.
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    Chapter 9 Identifying RBP Targets with RIP-seq.
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    Chapter 10 PAR-CLIP: A Method for Transcriptome-Wide Identification of RNA Binding Protein Interaction Sites.
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    Chapter 11 Profiling the Binding Sites of RNA-Binding Proteins with Nucleotide Resolution Using iCLIP.
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    Chapter 12 A Pipeline for PAR-CLIP Data Analysis.
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    Chapter 13 Capture and Identification of miRNA Targets by Biotin Pulldown and RNA-seq.
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    Chapter 14 Post-Transcriptional Gene Regulation
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    Chapter 15 Genome-Wide Analysis of A-to-I RNA Editing.
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    Chapter 16 Nucleotide-Level Profiling of m5C RNA Methylation
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    Chapter 17 Probing N (6)-methyladenosine (m(6)A) RNA Modification in Total RNA with SCARLET.
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    Chapter 18 Genome-Wide Identification of Alternative Polyadenylation Events Using 3'T-Fill.
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    Chapter 19 Genome-Wide Profiling of Alternative Translation Initiation Sites.
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    Chapter 20 Post-Transcriptional Gene Regulation
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    Chapter 21 Visualizing mRNA Dynamics in Live Neurons and Brain Tissues.
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    Chapter 22 Single-Molecule Live-Cell Visualization of Pre-mRNA Splicing.
Attention for Chapter 8: Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.
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Chapter title
Comprehensive Identification of RNA-Binding Proteins by RNA Interactome Capture.
Chapter number 8
Book title
Post-Transcriptional Gene Regulation
Published in
Methods in molecular biology, January 2016
DOI 10.1007/978-1-4939-3067-8_8
Pubmed ID
Book ISBNs
978-1-4939-3066-1, 978-1-4939-3067-8
Authors

Alfredo Castello, Rastislav Horos, Claudia Strein, Bernd Fischer, Katrin Eichelbaum, Lars M. Steinmetz, Jeroen Krijgsveld, Matthias W. Hentze

Editors

Erik Dassi

Abstract

RNA associates with RNA-binding proteins (RBPs) from synthesis to decay, forming dynamic ribonucleoproteins (RNPs). In spite of the preeminent role of RBPs regulating RNA fate, the scope of cellular RBPs has remained largely unknown. We have recently developed a novel and comprehensive method to identify the repertoire of active RBPs of cultured cells, called RNA interactome capture. Using in vivo UV cross-linking on cultured cells, proteins are covalently bound to RNA if the contact between the two is direct ("zero distance"). Protein-RNA complexes are purified by poly(A) tail-dependent oligo(dT) capture and analyzed by quantitative mass spectrometry. Because UV irradiation is applied to living cells and purification is performed using highly stringent washes, RNA interactome capture identifies physiologic and direct protein-RNA interactions. Applied to HeLa cells, this protocol revealed the near-complete repertoire of RBPs, including hundreds of novel RNA binders. Apart from its RBP discovery capacity, quantitative and comparative RNA interactome capture can also be used to study the responses of the RBP repertoire to different physiological cues and processes, including metabolic stress, differentiation, development, or the response to drugs.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 213 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 <1%
Brazil 1 <1%
Italy 1 <1%
Sweden 1 <1%
Belgium 1 <1%
Unknown 207 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 63 30%
Researcher 51 24%
Student > Master 20 9%
Student > Bachelor 16 8%
Student > Doctoral Student 10 5%
Other 26 12%
Unknown 27 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 85 40%
Agricultural and Biological Sciences 63 30%
Medicine and Dentistry 8 4%
Immunology and Microbiology 5 2%
Neuroscience 5 2%
Other 14 7%
Unknown 33 15%