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Plant Genomics

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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 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
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Chapter title
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
Chapter number 19
Book title
Plant Genomics
Published in
Methods in molecular biology, April 2017
DOI 10.1007/978-1-4939-7003-2_19
Pubmed ID
Book ISBNs
978-1-4939-7001-8, 978-1-4939-7003-2
Authors

Elodie Vandelle, Maria Rita Puttilli, Andrea Chini, Giulia Devescovi, Vittorio Venturi, Annalisa Polverari

Editors

Wolfgang Busch

Abstract

The life cycle of bacterial phytopathogens consists of a benign epiphytic phase, during which the bacteria grow in the soil or on the plant surface, and a virulent endophytic phase involving the penetration of host defenses and the colonization of plant tissues. Innovative strategies are urgently required to integrate copper treatments that control the epiphytic phase with complementary tools that control the virulent endophytic phase, thus reducing the quantity of chemicals applied to economically and ecologically acceptable levels. Such strategies include targeted treatments that weaken bacterial pathogens, particularly those inhibiting early infection steps rather than tackling established infections. This chapter describes a reporter gene-based chemical genomic high-throughput screen for the induction of bacterial virulence by plant molecules. Specifically, we describe a chemical genomic screening method to identify agonist and antagonist molecules for the induction of targeted bacterial virulence genes by plant extracts, focusing on the experimental controls required to avoid false positives and thus ensuring the results are reliable and reproducible.

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 67%
Professor > Associate Professor 1 33%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 67%
Biochemistry, Genetics and Molecular Biology 1 33%