Skip to main content
ARS Home » Pacific West Area » Corvallis, Oregon » National Clonal Germplasm Repository » Research » Publications at this Location » Publication #255423

Title: Standardized plant disease evaluations will enhance resistance gene discovery

item Postman, Joseph
item Volk, Gayle
item ALDWINCKLE, HERB - Cornell University - New York

Submitted to: HortScience
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/18/2010
Publication Date: 9/20/2010
Citation: Postman, J.D., Volk, G.M., Aldwinckle, H. 2010. Standardized plant disease evaluations will enhance resistance gene discovery. HortScience. 45(9):1317-1320.

Interpretive Summary: The development of DNA based tools for discovering unique traits in plants requires access to plant populations that have been characterized for those traits. Once a trait-associated gene has been discovered in one crop, that gene may also be associated with the same trait in other related or unrelated crops. Databases that associate traits with particular plant species or cultivars, especially databases at national genebanks, may be inconsistent in how plant character data is stored. For example, researchers evaluating apples for fire blight resistance may use a scale of 1-5, while pear researchers use a scale of 1-9 to evaluate the same trait. In some studies a high number indicates high resistance, in others high susceptibility. Other reports may categorize trees as having greater or lesser resistance than a standard cultivar. Inconsistent data standards make it difficult for researchers to search databases for plants with similar characters. Before disease resistance traits can be associated with genetic (DNA) data, the rating scales and evaluation environments must be standardized to the extent possible. A standardized disease rating system is proposed using a scale of 1-9 with higher numbers indicating increased disease susceptibility.

Technical Abstract: Gene discovery and marker development using DNA-based tools require plant populations with well documented phenotypes. If dissimilar phenotype evaluation methods or data scoring techniques are employed with different crops, or at different labs for the same crops, then data mining for genetic marker correlations is challenging. For example, apples and pears may share many of the same disease resistance genes. Fire blight resistance evaluations for apples often use a scale of 1-5 and pear evaluations use a scale of 1-9. In some reports, a low number means low susceptibility and in other reports a low number means low resistance. Other disease evaluations rate resistance as greater than or less than a well documented standard cultivar. Environment, pathogen isolate and whether disease ratings are the result of natural infection or artificial inoculation also have a strong impact on disease resistance ratings. Before a wider set of disease resistance phenotype data can be correlated with genetic data, rating scales must be standardized and the evaluation environment must be taken into account. Standardizing the recording of disease resistance data in plant phenotype databases will improve the ability to correlate this data with genomic data.