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Plant Genomics

Overview of attention for book
Cover of 'Plant Genomics'

Table of Contents

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    Book Overview
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    Chapter 1 CRISPR/Cas-Mediated In Planta Gene Targeting
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    Chapter 2 User Guide for the LORE1 Insertion Mutant Resource
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    Chapter 3 Enabling Reverse Genetics in Medicago truncatula Using High-Throughput Sequencing for Tnt1 Flanking Sequence Recovery
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    Chapter 4 The Generation of Doubled Haploid Lines for QTL Mapping
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    Chapter 5 Assessing Distribution and Variation of Genome-Wide DNA Methylation Using Short-Read Sequencing
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    Chapter 6 Circular Chromosome Conformation Capture in Plants
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    Chapter 7 Genome-Wide Profiling of Histone Modifications and Histone Variants in Arabidopsis thaliana and Marchantia polymorpha
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    Chapter 8 Tissue-Specific Transcriptome Profiling in Arabidopsis Roots
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    Chapter 9 Sample Preparation Protocols for Protein Abundance, Acetylome, and Phosphoproteome Profiling of Plant Tissues
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    Chapter 10 Automated High-Throughput Root Phenotyping of Arabidopsis thaliana Under Nutrient Deficiency Conditions
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    Chapter 11 Large-Scale Phenotyping of Root Traits in the Model Legume Lotus japonicus
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    Chapter 12 Long-Term Confocal Imaging of Arabidopsis thaliana Roots for Simultaneous Quantification of Root Growth and Fluorescent Signals
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    Chapter 13 Identification of Protein–DNA Interactions Using Enhanced Yeast One-Hybrid Assays and a Semiautomated Approach
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    Chapter 14 Mapping Protein-Protein Interaction Using High-Throughput Yeast 2-Hybrid
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    Chapter 15 Mapping Protein–Protein Interactions Using Affinity Purification and Mass Spectrometry
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    Chapter 16 Measuring Protein Movement, Oligomerization State, and Protein-Protein Interaction in Arabidopsis Roots Using Scanning Fluorescence Correlation Spe..
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    Chapter 17 Studying Protein–Protein Interactions In Planta Using Advanced Fluorescence Microscopy
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    Chapter 18 Chemiluminescence-Based Detection of Peptide Activity and Peptide-Receptor Binding in Plants
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    Chapter 19 Application of Chemical Genomics to Plant–Bacteria Communication: A High-Throughput System to Identify Novel Molecules Modulating the Induction of Bacterial Virulence Genes by Plant Signals
Attention for Chapter 15: Mapping Protein–Protein Interactions Using Affinity Purification and Mass Spectrometry
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Citations

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Chapter title
Mapping Protein–Protein Interactions Using Affinity Purification and Mass Spectrometry
Chapter number 15
Book title
Plant Genomics
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-7003-2_15
Pubmed ID
28439867
Book ISBNs
978-1-4939-7001-8, 978-1-4939-7003-2
Authors

Chin-Mei Lee, Christopher Adamchek, Ann Feke, Dmitri A. Nusinow, Joshua M. Gendron

Editors

Wolfgang Busch

Abstract

The mapping of protein-protein interaction (PPI) networks and their dynamics are crucial steps to deciphering the function of a protein and its role in cellular pathways, making it critical to have comprehensive knowledge of a protein's interactome. Advances in affinity purification and mass spectrometry technology (AP-MS) have provided a powerful and unbiased method to capture higher-order protein complexes and decipher dynamic PPIs. However, the unbiased calling of nonspecific interactions and the ability to detect transient interactions remains challenging when using AP-MS, thereby hampering the detection of biologically meaningful complexes. Additionally, there are plant-specific challenges with AP-MS, such as a lack of protein-specific antibodies, which must be overcome to successfully identify PPIs. Here we discuss and describe a protocol designed to bypass the traditional challenges of AP-MS and provide a roadmap to identify bona fide PPIs in plants.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 43 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 8 19%
Student > Ph. D. Student 8 19%
Student > Master 7 16%
Researcher 6 14%
Professor > Associate Professor 3 7%
Other 1 2%
Unknown 10 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 33%
Agricultural and Biological Sciences 9 21%
Chemistry 4 9%
Computer Science 1 2%
Engineering 1 2%
Other 0 0%
Unknown 14 33%

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