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MicroRNA Detection and Target Identification

Overview of attention for book
Cover of 'MicroRNA Detection and Target Identification'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Improved Denaturation of Small RNA Duplexes and Its Application for Northern Blotting
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    Chapter 2 High-Throughput RT-qPCR for the Analysis of Circulating MicroRNAs
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    Chapter 3 Genome-Wide Comparison of Next-Generation Sequencing and qPCR Platforms for microRNA Profiling in Serum
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    Chapter 4 Small RNA Profiling by Next-Generation Sequencing Using High-Definition Adapters
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    Chapter 5 Surface Acoustic Wave Lysis and Ion-Exchange Membrane Quantification of Exosomal MicroRNA
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    Chapter 6 Droplet Microfluidic Device Fabrication and Use for Isothermal Amplification and Detection of MicroRNA
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    Chapter 7 Interrogation of Functional miRNA–Target Interactions by CRISPR/Cas9 Genome Engineering
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    Chapter 8 Cell-Free Urinary MicroRNAs Expression in Small-Scale Experiments
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    Chapter 9 Peptide-Based Isolation of Argonaute Protein Complexes Using Ago-APP
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    Chapter 10 Predicting Functional MicroRNA-mRNA Interactions
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    Chapter 11 Computational and Experimental Identification of Tissue-Specific MicroRNA Targets
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    Chapter 12 sRNAtoolboxVM: Small RNA Analysis in a Virtual Machine
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    Chapter 13 An Assessment of the Next Generation of Animal miRNA Target Prediction Algorithms
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    Chapter 14 The UEA Small RNA Workbench: A Suite of Computational Tools for Small RNA Analysis
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    Chapter 15 Prediction of miRNA–mRNA Interactions Using miRGate
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    Chapter 16 Detection of microRNAs Using Chip-Based QuantStudio 3D Digital PCR
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    Chapter 17 MiRNA Quantitation with Microelectrode Sensors Enabled by Enzymeless Electrochemical Signal Amplification
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    Chapter 18 A Robust Protocol to Quantify Circulating Cancer Biomarker MicroRNAs
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    Chapter 19 MicroRNAs, Regulatory Networks, and Comorbidities: Decoding Complex Systems
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    Chapter 20 Label-Free Direct Detection of MiRNAs with Poly-Silicon Nanowire Biosensors
  22. Altmetric Badge
    Chapter 21 Erratum to: Cell-Free Urinary MicroRNAs Expression in Small-Scale Experiments
Attention for Chapter 7: Interrogation of Functional miRNA–Target Interactions by CRISPR/Cas9 Genome Engineering
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Chapter title
Interrogation of Functional miRNA–Target Interactions by CRISPR/Cas9 Genome Engineering
Chapter number 7
Book title
MicroRNA Detection and Target Identification
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-6866-4_7
Pubmed ID
Book ISBNs
978-1-4939-6864-0, 978-1-4939-6866-4
Authors

Yale S. Michaels, Qianxin Wu, Tudor A. Fulga, Michaels, Yale S., Wu, Qianxin, Fulga, Tudor A.

Editors

Tamas Dalmay

Abstract

Post-transcriptional silencing by microRNAs (miRNAs) is a critical constituent of eukaryotic gene regulation. miRNAs are short (~22nt) noncoding RNAs capable of specifically targeting the miRNA-induced-silencing-complex (miRISC) to transcripts bearing a complementary miRNA response element (MRE). Although recent methodological advances have greatly improved our understanding of miRNA biogenesis and the mechanisms by which miRNAs repress their cognate targets, exploring the physiological relevance of direct miRNA-target interactions in vivo has remained an outstanding challenge. Here we describe the experimental protocol underlying a novel approach, which allows direct interrogation of specific miRNA-MRE interactions by CRISPR/Cas9-mediated genome engineering. In this instance, the CRISPR/Cas9 system is first used to catalyze homology-directed replacement of candidate MREs with molecular barcodes at endogenous loci. Subsequently, the effect of MRE mutation on transcript abundance (i.e., MRE activity) can be rapidly evaluated by routine quantitative PCR. This strategy enables functional investigation of a putative miRNA-target pair in a pool of transiently transfected cells, obviating the need for generation of clonal cell lines or transgenic animals. This protocol can be implemented in any cell line in less than 2 weeks, and can readily be scaled up for multiplex studies. To facilitate the conceptual workflow underlying this strategy, we also describe a genome-wide resource for automated design and computational evaluation of CRISPR/Cas9 guide RNAs targeting all predicted MREs in various species (miR-CRISPR).

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X Demographics

The data shown below were collected from the profiles of 9 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 20%
Other 2 10%
Unspecified 1 5%
Student > Bachelor 1 5%
Student > Doctoral Student 1 5%
Other 2 10%
Unknown 9 45%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 25%
Agricultural and Biological Sciences 3 15%
Mathematics 1 5%
Unspecified 1 5%
Computer Science 1 5%
Other 1 5%
Unknown 8 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 01 May 2017.
All research outputs
#5,876,096
of 23,322,258 outputs
Outputs from Methods in molecular biology
#1,647
of 13,331 outputs
Outputs of similar age
#91,310
of 310,578 outputs
Outputs of similar age from Methods in molecular biology
#25
of 263 outputs
Altmetric has tracked 23,322,258 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 13,331 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 87% 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 310,578 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 70% of its contemporaries.
We're also able to compare this research output to 263 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.