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mRNA Decay

Overview of attention for book
Cover of 'mRNA Decay'

Table of Contents

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    Book Overview
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    Chapter 1 5′-Bromouridine IP Chase (BRIC)-Seq to Determine RNA Half-Lives
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    Chapter 2 Determining mRNA Decay Rates Using RNA Approach to Equilibrium Sequencing (RATE-Seq)
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    Chapter 3 Metabolic Labeling of Newly Synthesized RNA with 4sU to in Parallel Assess RNA Transcription and Decay
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    Chapter 4 Measuring mRNA Decay in Budding Yeast Using Single Molecule FISH
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    Chapter 5 PAR-CLIP for Discovering Target Sites of RNA-Binding Proteins
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    Chapter 6 Characterizing mRNA Sequence Motifs in the 3′-UTR Using GFP Reporter Constructs
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    Chapter 7 iCLIP of the PIWI Protein Aubergine in Drosophila Embryos
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    Chapter 8 Integration of ENCODE RNAseq and eCLIP Data Sets
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    Chapter 9 Identifying miRNA Targets Using AGO-RIPseq
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    Chapter 10 Integrated Analysis of miRNA and mRNA Expression Profiles to Identify miRNA Targets
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    Chapter 11 Identifying RISC Components Using Ago2 Immunoprecipitation and Mass Spectrometry
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    Chapter 12 Using Tet-Off Cells and RNAi Knockdown to Assay mRNA Decay
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    Chapter 13 Identifying Cellular Nonsense-Mediated mRNA Decay (NMD) Targets: Immunoprecipitation of Phosphorylated UPF1 Followed by RNA Sequencing (p-UPF1 RIP−Seq)
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    Chapter 14 Generation of Cell Lines Stably Expressing a Fluorescent Reporter of Nonsense-Mediated mRNA Decay Activity
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    Chapter 15 Reactivation Assay to Identify Direct Targets of the Nonsense-Mediated mRNA Decay Pathway in Drosophila
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    Chapter 16 Studying Nonsense-Mediated mRNA Decay in Mammalian Cells Using a Multicolored Bioluminescence-Based Reporter System
Attention for Chapter 13: Identifying Cellular Nonsense-Mediated mRNA Decay (NMD) Targets: Immunoprecipitation of Phosphorylated UPF1 Followed by RNA Sequencing (p-UPF1 RIP−Seq)
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Chapter title
Identifying Cellular Nonsense-Mediated mRNA Decay (NMD) Targets: Immunoprecipitation of Phosphorylated UPF1 Followed by RNA Sequencing (p-UPF1 RIP−Seq)
Chapter number 13
Book title
Methods in Molecular Biology
Published in
Methods in molecular biology, December 2017
DOI 10.1007/978-1-4939-7540-2_13
Pubmed ID
Book ISBNs
978-1-4939-7539-6, 978-1-4939-7540-2
Authors

Kurosaki, Tatsuaki, Hoque, Mainul, Maquat, Lynne E., Tatsuaki Kurosaki, Mainul Hoque, Lynne E. Maquat

Abstract

Recent progress in the technology of transcriptome-wide high-throughput sequencing has revealed that nonsense-mediated mRNA decay (NMD) targets ~10% of physiologic transcripts for the purpose of tuning gene expression in response to various environmental conditions. Regardless of the eukaryote studied, NMD requires the ATP-dependent RNA helicase upframeshift 1 (UPF1). It was initially thought that cellular NMD targets could be defined by their binding to steady-state UPF1, which is largely hypophosphorylated. However, the propensity for steady-state UPF1 to bind RNA nonspecifically, coupled with regulated phosphorylation of UPF1 on an NMD target serving as the trigger for NMD, made it clear that it is phosphorylated UPF1 (p-UPF1), rather than steady-state UPF1, that can be used to distinguish cellular NMD targets from cellular RNAs that are not. Here, we describe the immunoprecipitation of p-UPF1 followed by RNA sequencing (p-UPF1 RIP-seq) as a transcriptome-wide approach to define physiologic NMD targets.

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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 %
Researcher 6 24%
Student > Ph. D. Student 5 20%
Student > Doctoral Student 2 8%
Student > Bachelor 2 8%
Professor 1 4%
Other 2 8%
Unknown 7 28%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 36%
Agricultural and Biological Sciences 5 20%
Neuroscience 3 12%
Immunology and Microbiology 1 4%
Unknown 7 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 December 2017.
All research outputs
#14,960,787
of 23,011,300 outputs
Outputs from Methods in molecular biology
#4,729
of 13,157 outputs
Outputs of similar age
#252,713
of 439,309 outputs
Outputs of similar age from Methods in molecular biology
#522
of 1,523 outputs
Altmetric has tracked 23,011,300 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,157 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 59% 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 439,309 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,523 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 60% of its contemporaries.