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mRNA Processing

Overview of attention for book
Cover of 'mRNA Processing'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Detection and Identification of Uncapped RNA by Ligation-Mediated Reverse Transcription Polymerase Chain Reaction
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    Chapter 2 Preparation of Splicing Competent Nuclear Extract from Mammalian Cells and In Vitro Pre-mRNA Splicing Assay
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    Chapter 3 Single-Molecule Analysis of Pre-mRNA Splicing with Colocalization Single-Molecule Spectroscopy (CoSMoS)
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    Chapter 4 In Vitro Modulation of Endogenous Alternative Splicing Using Splice-Switching Antisense Oligonucleotides
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    Chapter 5 Purification of mRNA Processing Complexes Using an RNA Affinity Approach
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    Chapter 6 Polyadenylation Site-Based Analysis of Transcript Expression by 3′READS+
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    Chapter 7 Comprehensive Identification of mRNA Polyadenylation Sites by PAPERCLIP
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    Chapter 8 Microinjection and Fluorescence In Situ Hybridization Assay for Studying mRNA Export in Mammalian Cells
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    Chapter 9 Methods for the Detection of Adenosine-to-Inosine Editing Events in Cellular RNA
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    Chapter 10 Using RNA-Seq to Discover Genetic Polymorphisms That Produce Hidden Splice Variants
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    Chapter 11 Inducible Expression of Eukaryotic Circular RNAs from Plasmids
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    Chapter 12 Methods for Extraction of RNA, Proteins, or Protein Complexes from Subcellular Compartments of Eukaryotic Cells
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    Chapter 13 Isolation of Newly Transcribed RNA Using the Metabolic Label 4-Thiouridine
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    Chapter 14 Robust, Cost-Effective Profiling of RNA Binding Protein Targets with Single-end Enhanced Crosslinking and Immunoprecipitation (seCLIP)
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    Chapter 15 Purification of Transcript-Specific mRNP Complexes Formed In Vivo from Saccharomyces cerevisiae
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    Chapter 16 A Cell-Based High-Throughput Method for Identifying Modulators of Alternative Splicing
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    Chapter 17 Genome-Wide RNAi Screens for RNA Processing Events in Drosophila melanogaster S2 Cells
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    Chapter 18 Assaying RNA Structure Inside Living Cells with SHAPE
  20. Altmetric Badge
    Chapter 19 Erratum to: Robust, Cost-Effective Profiling of RNA Binding Protein Targets with Single-end Enhanced Crosslinking and Immunoprecipitation (seCLIP)
Attention for Chapter 9: Methods for the Detection of Adenosine-to-Inosine Editing Events in Cellular RNA
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  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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Chapter title
Methods for the Detection of Adenosine-to-Inosine Editing Events in Cellular RNA
Chapter number 9
Book title
mRNA Processing
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-7204-3_9
Pubmed ID
Book ISBNs
978-1-4939-7203-6, 978-1-4939-7204-3
Authors

Eimile Oakes, Pranathi Vadlamani, Heather A. Hundley

Abstract

Modification of RNA is essential for properly expressing the repertoire of RNA transcripts necessary for both cell type and developmental specific functions. RNA modifications serve to dynamically re-wire and fine-tune the genetic information carried by an invariable genome. One important type of RNA modification is RNA editing and the most common and well-studied type of RNA editing is the hydrolytic deamination of adenosine to inosine. Inosine is a biological mimic of guanosine; therefore, when RNA is reverse transcribed, inosine is recognized as guanosine by the reverse transcriptase and a cytidine is incorporated into the complementary DNA (cDNA) strand. During PCR amplification, guanosines pair with the newly incorporated cytidines. As a result, the adenosine-to-inosine (A-to-I) editing events are recognized as adenosine to guanosine changes when comparing the sequences of the genomic DNA to the cDNA. This chapter describes the methods for extracting endogenous RNA for subsequent analyses of A-to-I RNA editing using reverse transcriptase-based approaches. We discuss techniques for the detection of A-to-I RNA editing events in messenger RNA (mRNA), including analyzing editing levels at specific adenosines within the total pool of mRNA versus analyzing editing patterns that occur in individual transcripts and a method for detecting editing events across the entire transcriptome. The detection of RNA editing events and editing levels can be used to better understand normal biological processes and disease states.

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 25 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 36%
Student > Bachelor 4 16%
Student > Doctoral Student 3 12%
Researcher 2 8%
Other 1 4%
Other 2 8%
Unknown 4 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 36%
Agricultural and Biological Sciences 5 20%
Immunology and Microbiology 1 4%
Sports and Recreations 1 4%
Medicine and Dentistry 1 4%
Other 3 12%
Unknown 5 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 August 2017.
All research outputs
#12,756,285
of 22,996,001 outputs
Outputs from Methods in molecular biology
#3,172
of 13,151 outputs
Outputs of similar age
#195,205
of 421,191 outputs
Outputs of similar age from Methods in molecular biology
#292
of 1,074 outputs
Altmetric has tracked 22,996,001 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,151 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 75% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 421,191 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.