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Plant-Pathogen Interactions

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

Table of Contents

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    Book Overview
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    Chapter 1 Specific Detection and Quantification of Major Fusarium spp. Associated with Cereal and Pulse Crops
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    Chapter 2 Distinguishing Puccinia striiformis f. sp. tritici Isolates Using Genomic Sequencing: A Case Study
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    Chapter 3 DNA-Barcoding Identification of Plant Pathogens for Disease Diagnostics
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    Chapter 4 Real-Time Portable LAMP Assay for a Rapid Detection of Xylella fastidiosa In-Field
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    Chapter 5 Selective Quantification of Chemotropic Responses of Fusarium graminearum
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    Chapter 6 Live-Cell Visualization of Early Stages of Root Colonization by the Vascular Wilt Pathogen Fusarium oxysporum
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    Chapter 7 Transfection of Barley Leaf Protoplasts with a Fluorescently Tagged Fungal Effector for In Planta Localization Studies in Barley
  9. Altmetric Badge
    Chapter 8 A Bioinformatic Guide to Identify Protein Effectors from Phytopathogens
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    Chapter 9 Unraveling Plant-Pathogen Interactions in Cereals Using RNA-seq.
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    Chapter 10 RNA-Seq Data Processing in Plant-Pathogen Interaction System: A Case Study
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    Chapter 11 Differential Expression Feature Extraction (DEFE): A Case Study in Wheat FHB RNA-Seq Data Analysis
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    Chapter 12 Proteomic Profiling of Host Response in the Cereal Crop Triticum aestivum to the Mycotoxin, 15-Acetyldeoxynivalenol, Produced by the Fungal Pathogen, Fusarium graminearum
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    Chapter 13 Quantitative Phosphoproteome Analysis of the Interaction Between Fusarium graminearum and Triticum aestivum
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    Chapter 14 Fatty Acid Profiling of Grapevine Extracellular Compartment
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    Chapter 15 Identifying Fungal Secondary Metabolites and Their Role in Plant Pathogenesis
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    Chapter 16 Eliciting Targeted Mutations in Medicago sativa Using CRISPR/Cas9-Mediated Genome Editing: A Potential Tool for the Improvement of Disease Resistance
Attention for Chapter 9: Unraveling Plant-Pathogen Interactions in Cereals Using RNA-seq.
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Chapter title
Unraveling Plant-Pathogen Interactions in Cereals Using RNA-seq.
Chapter number 9
Book title
Plant-Pathogen Interactions
Published in
Methods in molecular biology, January 2023
DOI 10.1007/978-1-0716-3159-1_9
Pubmed ID
Book ISBNs
978-1-07-163158-4, 978-1-07-163159-1
Authors

Rowland, Bronwyn E, Henriquez, Maria Antonia, Nilsen, Kirby T, Subramaniam, Rajagopal, Walkowiak, Sean, Rowland, Bronwyn E., Nilsen, Kirby T.

Abstract

Over the past two decades, there have been significant advancements in the realm of transcriptomics, or the study of genes and their expression. Modern RNA sequencing technologies and high-performance computing are creating a "big data" revolution that provides new opportunities to explore the interactions between cereals and pathogens that affect grain yield and food safety. These data are being used to annotate genes and gene variants, as well as identify differentially expressed genes and create global gene co-expression networks. Moreover, these data can unravel the complex interactions between pathogen and host and identify genes and pathways involved in these interactions. This information can then be used for disease mitigation and the development of crops with superior resistance.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Student > Master 1 25%
Unknown 2 50%
Readers by discipline Count As %
Unspecified 1 25%
Biochemistry, Genetics and Molecular Biology 1 25%
Unknown 2 50%
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 30 May 2023.
All research outputs
#21,169,343
of 26,004,690 outputs
Outputs from Methods in molecular biology
#9,248
of 14,508 outputs
Outputs of similar age
#357,857
of 482,853 outputs
Outputs of similar age from Methods in molecular biology
#529
of 715 outputs
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We're also able to compare this research output to 715 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.