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Plant-Pathogen Interactions

Overview of attention for book
Cover of 'Plant-Pathogen Interactions'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Galaxy as a platform for identifying candidate pathogen effectors.
  3. Altmetric Badge
    Chapter 2 Bioinformatic analysis of expression data to identify effector candidates.
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    Chapter 3 Two-Dimensional Data Binning for the Analysis of Genome Architecture in Filamentous Plant Pathogens and Other Eukaryotes
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    Chapter 4 On the statistics of identifying candidate pathogen effectors.
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    Chapter 5 High-Throughput Imaging of Plant Immune Responses
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    Chapter 6 In Vivo Protein-Protein Interaction Studies with BiFC: Conditions, Cautions, and Caveats.
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    Chapter 7 Particle bombardment-mediated transient expression to identify localization signals in plant disease resistance proteins and target sites for the proteolytic activity of pathogen effectors.
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    Chapter 8 Purification of Fungal Haustoria from Infected Plant Tissue by Flow Cytometry
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    Chapter 9 Functional characterization of nematode effectors in plants.
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    Chapter 10 Silencing of Aphid Genes by Feeding on Stable Transgenic Arabidopsis thaliana.
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    Chapter 11 Leaf-Disc Assay Based on Transient Over-Expression in Nicotiana benthamiana to Allow Functional Screening of Candidate Effectors from Aphids.
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    Chapter 12 A Growth Quantification Assay for Hyaloperonospora arabidopsidis Isolates in Arabidopsis thaliana
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    Chapter 13 Simple Quantification of In Planta Fungal Biomass
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    Chapter 14 Virus-Induced Gene Silencing and Agrobacterium tumefaciens-Mediated Transient Expression in Nicotiana tabacum
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    Chapter 15 DIGE-ABPP by Click Chemistry: Pairwise Comparison of Serine Hydrolase Activities from the Apoplast of Infected Plants.
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    Chapter 16 A Simple and Fast Protocol for the Protein Complex Immunoprecipitation (Co-IP) of Effector: Host Protein Complexes
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    Chapter 17 An Arabidopsis and Tomato Mesophyll Protoplast System for Fast Identification of Early MAMP-Triggered Immunity-Suppressing Effectors
  19. Altmetric Badge
    Chapter 18 Production of RXLR Effector Proteins for Structural Analysis by X-Ray Crystallography
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    Chapter 19 The Do's and Don'ts of Effectoromics.
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    Chapter 20 Protoplast Cell Death Assay to Study Magnaporthe oryzae AVR Gene Function in Rice
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    Chapter 21 A Bacterial Type III Secretion-Based Delivery System for Functional Assays of Fungal Effectors in Cereals
  23. Altmetric Badge
    Chapter 22 Genomic DNA Library Preparation for Resistance Gene Enrichment and Sequencing (RenSeq) in Plants.
Attention for Chapter 19: The Do's and Don'ts of Effectoromics.
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Chapter title
The Do's and Don'ts of Effectoromics.
Chapter number 19
Book title
Plant-Pathogen Interactions
Published in
Methods in molecular biology, March 2014
DOI 10.1007/978-1-62703-986-4_19
Pubmed ID
Book ISBNs
978-1-62703-985-7, 978-1-62703-986-4
Authors

Du J, Vleeshouwers VG, Juan Du, Vivianne G. A. A. Vleeshouwers, Du, Juan, Vleeshouwers, Vivianne G. A. A.

Abstract

Effectoromics, a high-throughput functional genomics approach that uses effectors to probe plant germplasm to detect R genes, has proven a potent contribution to modern resistance breeding. Advantages of effectoromics are summarized in four aspects: (1) accelerating R gene identification; (2) distinguishing functional redundancy; (3) detecting recognition specificity and (4) assisting in R gene deployment. In this manuscript, we provide suggestions as well as some reminders for applying effectoromics in the breeding process. The two routine functional assays that are widely used, agroinfiltration and agroinfection, are presented. We briefly explain their advantages and disadvantages and provide protocols for applying them in the model system Nicotiana benthamiana as well as in potato (Solanum tuberosum).

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The data shown below were collected from the profiles of 2 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 17%
Student > Ph. D. Student 8 17%
Researcher 7 15%
Student > Bachelor 4 9%
Student > Doctoral Student 3 7%
Other 5 11%
Unknown 11 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 59%
Biochemistry, Genetics and Molecular Biology 6 13%
Unspecified 1 2%
Immunology and Microbiology 1 2%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 10 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 22 April 2020.
All research outputs
#17,731,162
of 22,769,322 outputs
Outputs from Methods in molecular biology
#7,189
of 13,090 outputs
Outputs of similar age
#154,656
of 223,432 outputs
Outputs of similar age from Methods in molecular biology
#48
of 156 outputs
Altmetric has tracked 22,769,322 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,090 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
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We're also able to compare this research output to 156 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 66% of its contemporaries.