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Promoter Associated RNA

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Cover of 'Promoter Associated RNA'

Table of Contents

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    Book Overview
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    Chapter 1 ChIP-seq for the Identification of Functional Elements in the Human Genome
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    Chapter 2 Identification of Candidate Functional Elements in the Genome from ChIP-seq Data
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    Chapter 3 GRO-seq, A Tool for Identification of Transcripts Regulating Gene Expression
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    Chapter 4 NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
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    Chapter 5 Deep Cap Analysis of Gene Expression (CAGE): Genome-Wide Identification of Promoters, Quantification of Their Activity, and Transcriptional Network Inference
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    Chapter 6 Deep-RACE: Comprehensive Search for Novel ncRNAs Associated to a Specific Locus
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    Chapter 7 In Silico Prediction of RNA Secondary Structure
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    Chapter 8 Computational Prediction of RNA-Protein Interactions
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    Chapter 9 Isolation of Nuclear RNA-Associated Protein Complexes
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    Chapter 10 Identification of Long Noncoding RNAs Associated to Human Disease Susceptibility
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    Chapter 11 Targeting Promoter-Associated RNAs by siRNAs
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    Chapter 12 RNA-FISH to Study Regulatory RNA at the Site of Transcription
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    Chapter 13 Detection and Characterization of R Loop Structures
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    Chapter 14 Induction of Transcriptional Gene Silencing by Expression of shRNA Directed to c-Myc P2 Promoter in Hepatocellular Carcinoma by Tissue-Specific Virosomal Delivery
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    Chapter 15 Targeting Promoter-Associated Noncoding RNA In Vivo
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    Chapter 16 Manipulation of Promoter-Associated Noncoding RNAs in Mouse Early Embryos for Controlling Sequence-Specific Epigenetic Status
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    Chapter 17 Erratum to: NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
Attention for Chapter 13: Detection and Characterization of R Loop Structures
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Chapter title
Detection and Characterization of R Loop Structures
Chapter number 13
Book title
Promoter Associated RNA
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6716-2_13
Pubmed ID
Book ISBNs
978-1-4939-6714-8, 978-1-4939-6716-2
Authors

Raquel Boque-Sastre, Marta Soler, Sonia Guil

Editors

Sara Napoli

Abstract

R loops are special three stranded nucleic acid structures that comprise a nascent RNA hybridized with the DNA template strand, leaving a non-template DNA single-stranded. More specifically, R loops form in vivo as G-rich RNA transcripts invade the DNA duplex and anneal to the template strand to generate an RNA:DNA hybrid, leaving the non-template, G-rich DNA strand in a largely single-stranded conformation (Aguilera and Garcia-Muse, Mol Cell 46:115-124, 2012).DNA-RNA hybrids are a natural occurrence within eukaryotic cells, with levels of these hybrids increasing at sites with high transcriptional activity, such as during transcription initiation, repression, and elongation. RNA-DNA hybrids influence genomic instability, and growing evidence points to an important role for R loops in active gene expression regulation (Ginno et al., Mol Cell 45, 814-825, 2012; Sun et al., Science 340: 619-621, 2013; Bhatia et al., Nature 511, 362-365, 2014). Analysis of the occurrence of such structures is therefore of increasing relevance and herein we describe methods for the in vivo and in vitro identification and characterization of R loops in mammalian systems.R loops (DNA:RNA hybrids and the associated single-stranded DNA) have been traditionally associated with threats to genome integrity, making some regions of the genome more prone to DNA-damaging and mutagenic agents. Initially considered to be rare byproducts of transcription, over the last decade accumulating evidence has pointed to a new view in which R loops form more frequently than previously thought. The R loop field has become an increasingly expanded area of research, placing these structures as a major threat to genome stability but also as potential regulators of gene expression. Special interest has arisen as they have also been linked to a variety of diseases, including neurological disorders and cancer, positioning them as potential therapeutic targets [5].

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Mendeley readers

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 48 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 25%
Student > Ph. D. Student 8 17%
Student > Postgraduate 5 10%
Student > Master 4 8%
Student > Bachelor 3 6%
Other 7 15%
Unknown 9 19%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 33 69%
Agricultural and Biological Sciences 2 4%
Immunology and Microbiology 1 2%
Chemistry 1 2%
Materials Science 1 2%
Other 0 0%
Unknown 10 21%