Title: Standardized Plant Disease Evaluations will Enhance Resistance Gene Discovery Authors
Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: April 10, 2009
Publication Date: June 20, 2009
Citation: Postman, J.D., Aldwinckle, H., Volk, G.M. 2009. Standardized Plant Disease Evaluations will Enhance Resistance Gene Discovery. Meeting Proceedings. HortScience 44:975. 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. Related crops such as apples and pears may share a number of genes, for example resistance to common diseases, and data mining in one crop may reveal genes for the other. However, unless consistent phenotype evaluation methods or data scoring techniques are employed, data mining for marker-trait associations is difficult. Fire blight resistance evaluations for apples may use a scale of 1-5 and pear evaluations may use 1-9. Some reports use a low numerical rating to indicate low susceptibility and others to indicate low resistance. Still others may report disease resistance as greater than or less than that of a standard cultivar. Environment, pathogen isolate and whether disease ratings are the result of natural infection or artificial inoculation also have strong impacts on disease resistance ratings. Before disease resistance phenotype data can be correlated with genetic data, the rating scale and evaluation environment must be standardized to the extent possible. Examples of pome fruit disease evaluations will be presented and a standardized disease rating system will be proposed.