Skip to main content
ARS Home » Research » Publications at this Location » Publication #155117

Title: EXPLORING THE RELATIONSHIP BETWEEN ALLELES AND EPIDEMICS: THE CASE OF POTATO LATE BLIGHT

Author
item Grunwald, Niklaus - Nik

Submitted to: Phytopathology
Publication Type: Abstract Only
Publication Acceptance Date: 1/1/2003
Publication Date: 6/1/2003
Citation: GRUNWALD, N.J. EXPLORING THE RELATIONSHIP BETWEEN ALLELES AND EPIDEMICS: THE CASE OF POTATO LATE BLIGHT. PHYTOPATHOLOGY. 2003. 93:S107.

Interpretive Summary:

Technical Abstract: In analogy to population biologists (studying gene frequencies) and ecologists (studying frequencies of individuals), plant pathologists specializing in either the epidemiology or population biology of plant pathogens have developed two separate disciplines utilizing different sets of tools. Typically, epidemiologists study what factors are responsible for changes and development of disease severity or particular phenotype frequencies; population biologists study what factors, such as gene flow or selection, are responsible for changes in allele or gene frequencies. Both approaches are two sides of the same coin, and often can reveal only parts of the mechanisms underlying the observed reality if the other discipline is not taken into consideration. Alleles exist within individuals. Phenotypes result from a certain combination of alleles/genes within individuals interacting with the environment. To take an example from both disciplines, fungicide resistance can be based on a single gene. In this extreme case, a population biologist studying frequency of the gene for fungicide resistance and the epidemiologist studying frequency of phenotype for fungicide resistance will both study units where phenotypes and genotypes are identical. This paper will explore the interface between population biology and epidemiology using the case of potato late blight. In particular, the dynamics of host-pathogen coevolution where hosts exhibit both quantitative and gene-for-gene resistance will be explored. This modeling effort, integrating both disciplines, shows that both approaches need to be integrated to fully understand the biology of this particular system.