Field Pathogenomics: An Advanced Tool for Wheat Rust Surveillance View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017

AUTHORS

Vanessa Bueno-Sancho , Daniel C. E. Bunting , Luis J. Yanes , Kentaro Yoshida , Diane G. O. Saunders

ABSTRACT

Traditionally, diagnostic tools for plant pathogens were limited to the analysis of purified pathogen isolates subjected to phenotypic characterization and/or PCR-based genotypic analysis. However, these approaches detect only already known pathogenic agents, may not always recognize novel races, and can introduce bias in the results. Recent advances in next-generation sequencing technologies have provided new opportunities to integrate high-resolution genotype data into pathogen surveillance programs. Here, we describe some of the key bioinformatics analysis used in the newly developed "Field Pathogenomics" pathogen surveillance technique. This technique is based on RNA-seq data generated directly form pathogen-infected plant leaf samples collected in the field, providing a unique opportunity to characterize the pathogen population and its host directly in their natural environment. We describe two main analyses: (1) a phylogenetic analysis of the pathogen isolates that have been collected to understand how they are related to each other, and (2) a population structure analysis to provide insight into the genetic substructure within the pathogen population. This provides a high-resolution representation of pathogen population dynamics directly in the field, providing new insights into pathogen biology, population structure, and pathogenesis. More... »

PAGES

13-28

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4939-7249-4_2

DOI

http://dx.doi.org/10.1007/978-1-4939-7249-4_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091393155

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28856637


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