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Functional Variation of Plant-Pathogen Interactions: New Concept and Methods for Virulence Data Analyses.

E Kosman1, X Chen2, A Dreiseitl3

  • 11Institute for Cereal Crops Improvement, Tel Aviv University, Tel Aviv 69978, Israel.

Phytopathology
|April 9, 2019
PubMed
Summary

Traditional virulence analysis uses binary data, but infection type (IT) data offers a richer view. New methods analyzing IT phenotypes reveal functional variation in plant-pathogen interactions, improving epidemic studies.

Keywords:
analytical and theoretical plant pathologyecology and epidemiologygenetics and resistancepopulation biology

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Area of Science:

  • Plant Pathology
  • Population Genetics
  • Epidemiology

Background:

  • Classical virulence analysis relies on binary genetic data (virulence/avirulence).
  • This binary approach often overlooks functional variation in pathogen isolates.
  • Population genetics tools are standard for analyzing multi-locus virulence data.

Purpose of the Study:

  • To introduce and evaluate new methods for analyzing functional variation using infection type (IT) data.
  • To explore the utility of IT phenotypes beyond traditional binary virulence assessments.
  • To demonstrate the potential of IT-based analysis for understanding plant-pathogen interactions and epidemics.

Main Methods:

  • Development of novel methods to measure functional variation from host-pathogen IT data.
  • Utilizing expert-assessed dissimilarity scales for IT scores specific to plant-pathogen systems.
  • Comparative analysis of results from IT phenotypes versus binary virulence phenotypes.

Main Results:

  • IT data provides a more detailed assessment of pathogen functional traits than binary phenotypes.
  • New methods allow for the quantification of functional variation within and among pathogen populations.
  • Discrepancies were observed between IT-based and binary virulence-based analyses, highlighting the limitations of the latter.

Conclusions:

  • Analyzing functional variation with IT data offers a more comprehensive understanding of plant-pathogen interactions.
  • This approach can reveal environmental components of pathogen variation alongside genetic factors.
  • IT-based variation measurement is a promising tool for studying plant pathogen epidemics.