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Argonaute Proteins

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Cover of 'Argonaute Proteins'

Table of Contents

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    Book Overview
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    Chapter 1 Cloning and Identification of Recombinant Argonaute-Bound Small RNAs Using Next-Generation Sequencing
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    Chapter 2 Quantification of miRNAs Co-Immunoprecipitated with Argonaute Proteins Using SYBR Green-Based qRT-PCR
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    Chapter 3 Gateway to Understanding Argonaute Loading of Single-Stranded RNAs: Preparation of Deep Sequencing Libraries with In Vitro Loading Samples
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    Chapter 4 Dumbbell-PCR for Discriminative Quantification of a Small RNA Variant
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    Chapter 5 MicroRNA Detection by Whole-Mount In Situ Hybridization in C. elegans
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    Chapter 6 cCLIP-Seq: Retrieval of Chimeric Reads from HITS-CLIP (CLIP-Seq) Libraries
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    Chapter 7 Kinetic Analysis of Small Silencing RNA Production by Human and Drosophila Dicer Enzymes In Vitro
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    Chapter 8 Nucleic Acid-Binding Assay of Argonaute Protein Using Fluorescence Polarization
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    Chapter 9 Reconstitution of RNA Interference Machinery
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    Chapter 10 Single-Molecule Analysis for RISC Assembly and Target Cleavage
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    Chapter 11 Profiling Open Chromatin Structure in the Ovarian Somatic Cells Using ATAC-seq
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    Chapter 12 Assessing miR-451 Activity and Its Role in Erythropoiesis
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    Chapter 13 Functional Analysis of MicroRNAs in Neurogenesis During Mouse Cortical Development
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    Chapter 14 Cellular Approaches in Investigating Argonaute2-Dependent RNA Silencing
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    Chapter 15 Genomic Tagging of AGO1 Using CRISPR/Cas9-Mediated Homologous Recombination
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    Chapter 16 Accurate Profiling and Quantification of tRNA Fragments from RNA-Seq Data: A Vade Mecum for MINTmap
Attention for Chapter 3: Gateway to Understanding Argonaute Loading of Single-Stranded RNAs: Preparation of Deep Sequencing Libraries with In Vitro Loading Samples
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Chapter title
Gateway to Understanding Argonaute Loading of Single-Stranded RNAs: Preparation of Deep Sequencing Libraries with In Vitro Loading Samples
Chapter number 3
Book title
Argonaute Proteins
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7339-2_3
Pubmed ID
Book ISBNs
978-1-4939-7338-5, 978-1-4939-7339-2
Authors

Eling Goh, Katsutomo Okamura

Abstract

Identification of sequences preferred by individual RNA-binding proteins (RBPs) has been accelerated by recent advances in the quantitative analysis of protein-RNA interactions on a massive scale, and such experiments have even revealed hidden sequence specificity of RBPs that were assumed to be non-specific. Argonaute (AGO) proteins bind diverse guide small RNAs and were believed to have no sequence specificity besides the preference for particular bases at the 5' nucleotide. However, we recently showed that short single-stranded RNAs (ssRNAs) are loaded to AGOs in vivo and in cell extracts with detectable sequence preferences. To study the sequence specificity, we established a protocol for preparing the oligo-specific deep-sequencing library. The protocol includes in vitro loading assay that uses RNA oligos containing randomized nucleotides at the first five positions and also splinted-ligation that specifically amplifies the introduced oligo RNA species from a complex mixture of endogenous small RNAs and exogenously introduced RNA oligos. With the current sequencing depth, this procedure will allow quantitative profiling of interactions between the AGO and ~1000 ssRNA species with different sequences. The method would aid in studying the mechanism behind the selective loading of ssRNAs to AGOs and may potentially be applied to study interactions between RNA and other RNA-binding proteins.

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Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 33%
Professor 1 17%
Professor > Associate Professor 1 17%
Student > Doctoral Student 1 17%
Unknown 1 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 3 50%
Agricultural and Biological Sciences 1 17%
Unknown 2 33%