↓ Skip to main content

Promoter Associated RNA

Overview of attention for book
Cover of 'Promoter Associated RNA'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 ChIP-seq for the Identification of Functional Elements in the Human Genome
  3. Altmetric Badge
    Chapter 2 Identification of Candidate Functional Elements in the Genome from ChIP-seq Data
  4. Altmetric Badge
    Chapter 3 GRO-seq, A Tool for Identification of Transcripts Regulating Gene Expression
  5. Altmetric Badge
    Chapter 4 NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
  6. Altmetric Badge
    Chapter 5 Deep Cap Analysis of Gene Expression (CAGE): Genome-Wide Identification of Promoters, Quantification of Their Activity, and Transcriptional Network Inference
  7. Altmetric Badge
    Chapter 6 Deep-RACE: Comprehensive Search for Novel ncRNAs Associated to a Specific Locus
  8. Altmetric Badge
    Chapter 7 In Silico Prediction of RNA Secondary Structure
  9. Altmetric Badge
    Chapter 8 Computational Prediction of RNA-Protein Interactions
  10. Altmetric Badge
    Chapter 9 Isolation of Nuclear RNA-Associated Protein Complexes
  11. Altmetric Badge
    Chapter 10 Identification of Long Noncoding RNAs Associated to Human Disease Susceptibility
  12. Altmetric Badge
    Chapter 11 Targeting Promoter-Associated RNAs by siRNAs
  13. Altmetric Badge
    Chapter 12 RNA-FISH to Study Regulatory RNA at the Site of Transcription
  14. Altmetric Badge
    Chapter 13 Detection and Characterization of R Loop Structures
  15. Altmetric Badge
    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
  16. Altmetric Badge
    Chapter 15 Targeting Promoter-Associated Noncoding RNA In Vivo
  17. Altmetric Badge
    Chapter 16 Manipulation of Promoter-Associated Noncoding RNAs in Mouse Early Embryos for Controlling Sequence-Specific Epigenetic Status
  18. Altmetric Badge
    Chapter 17 Erratum to: NanoCAGE: A Method for the Analysis of Coding and Noncoding 5′-Capped Transcriptomes
Attention for Chapter 3: GRO-seq, A Tool for Identification of Transcripts Regulating Gene Expression
Altmetric Badge

Readers on

mendeley
115 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Chapter title
GRO-seq, A Tool for Identification of Transcripts Regulating Gene Expression
Chapter number 3
Book title
Promoter Associated RNA
Published in
Methods in molecular biology, March 2017
DOI 10.1007/978-1-4939-6716-2_3
Pubmed ID
Book ISBNs
978-1-4939-6714-8, 978-1-4939-6716-2
Authors

Rui Lopes, Reuven Agami, Gozde Korkmaz

Editors

Sara Napoli

Abstract

The advent of next-generation sequencing (NGS) technologies has revolutionized the way we do research on gene expression. High-throughput transcriptomics became possible with the development of microarray technology, but its widespread application only occurred after the emergence of massive parallel sequencing. Especially, RNA sequencing (RNA-seq) has greatly increased our knowledge about the genome and led to the identification and annotation of novel classes of RNAs in different species. However, RNA-seq measures the steady-state level of a given RNA, which is the equilibrium between transcription, processing, and degradation. In recent years, a number of dedicated RNA-seq technologies were developed to measure specifically transcription events. Global run-on sequencing (GRO-seq) is the most widely used method to measure nascent RNA, and in recent years, it has been applied successfully to study the function and mechanism of action of noncoding RNAs. Here, we describe a detailed protocol of GRO-seq that can be readily applied to investigate different aspects of RNA biology in human cells.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 115 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 33%
Researcher 23 20%
Student > Bachelor 9 8%
Student > Master 7 6%
Student > Doctoral Student 5 4%
Other 16 14%
Unknown 17 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 56 49%
Agricultural and Biological Sciences 24 21%
Medicine and Dentistry 7 6%
Immunology and Microbiology 2 2%
Computer Science 2 2%
Other 3 3%
Unknown 21 18%