An unbiased method for the quantitation of disease phenotypes using a custom-built macro plugin for the program...

Area of Science:

• Plant pathology
• Molecular biology
• Bioinformatics

Background:

• Accurate plant disease phenotyping is crucial for understanding plant-microbe interactions and plant defense responses.
• Existing methods for quantifying infection are often unsuitable for large-scale disease screening.
• Visible disease symptoms reflect pathogen colonization and the plant's compromised defense.

Purpose of the Study:

• To develop an unbiased method for quantifying plant disease phenotypes suitable for high-throughput screening.
• To identify candidate host genes involved in plant resistance to pathogens.
• To provide a basis for unbiased identification of genes required for full resistance.

Main Methods:

• Utilized an ImageJ macro plugin to calculate disease indices based on visible symptoms.
• Employed a transgenic fungus expressing the GUS gene for clear pathogen detection via staining.
• Applied the method to analyze a functional silencing screen in resistant tomato inoculated with Cladosporium fulvum.

Main Results:

• The ImageJ macro plugin provides an unbiased quantification of disease phenotypes.
• GUS staining facilitated easy detection of the transgenic pathogen in high-throughput screens.
• The method successfully calculated disease indices for individual silenced plants.

Conclusions:

• The developed ImageJ macro plugin offers a versatile and unbiased approach for disease quantification.
• This method is effective for high-throughput screening and identifying plant resistance genes.
• The approach aids in discovering host genes essential for mounting effective defense responses against pathogens.