Host mating system and the prevalence of a disease in a plant population
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Abstract
A modified susceptible–infected–recovered (SIR) host–pathogen model is used to determine the influence of plant mating system on the outcome of a host–pathogen interaction. Unlike previous models describing how interactions between mating system and pathogen infection affect individual fitness, this model considers the potential consequences of varying mating systems on the prevalence of resistance alleles and disease within the population. If a single allele for disease resistance is sufficient to confer complete resistance in an individual and if both homozygote and heterozygote resistant individuals have the same mean birth and death rates, then, for any parameter set, the selfing rate does not affect the proportions of resistant, susceptible or infected individuals at equilibrium. If homozygote and heterozygote individual birth rates differ, however, the mating system can make a difference in these proportions. In that case, depending on other parameters, increased selfing can either increase or decrease the rate of infection in the population. Results from this model also predict higher frequencies of resistance alleles in predominantly selfing compared to predominantly outcrossing populations for most model conditions. In populations that have higher selfing rates, the resistance alleles are concentrated in homozygotes, whereas in more outcrossing populations, there are more resistant heterozygotes.
Publication type | Article |
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Publication Subtype | Journal Article |
Title | Host mating system and the prevalence of a disease in a plant population |
Series title | Proceedings of the Royal Society B |
DOI | 10.1098/rspb.2006.3519 |
Volume | 273 |
Issue | 1595 |
Year Published | 2006 |
Language | English |
Publisher | Royal Society Publishing |
Contributing office(s) | Southeast Ecological Science Center |
Description | 7 p. |
First page | 1825 |
Last page | 1831 |
Online Only (Y/N) | N |
Additional Online Files (Y/N) | N |
Google Analytic Metrics | Metrics page |