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Genetic epidemiology of the Sudden Oak Death pathogen Phytophthora ramorum in California

Authors


  • SM is a molecular biologist interested in the epidemiology and genetic basis of human and plant diseases, PC is an evolutionary biologist and statistical population geneticist interested in genetic epidemiology and the genomics of selection and adaptive radiation. MK is a doctoral student interested in evolutionary genetic of forest pathogens. LB is currently doctoral student at the University of Hawaii. MG is a mycologist and plant pathologist interested in the ecological and evolutionary consequences of the introduction of exotic diseases.

M. Garbelotto, Fax: +1 510 643 5436; E-mail: matteo@nature.berkeley.edu

Abstract

A total of 669 isolates of Phytophthora ramorum, the pathogen responsible for Sudden Oak Death, were collected from 34 Californian forests and from the ornamental plant-trade. Seven microsatellite markers revealed 82 multilocus genotypes (MGs) of which only three were abundant (>10%). Iteratively collapsing based upon minimum ΦST, yielded five meta-samples and five singleton populations. Populations in the same meta-sample were geographically contiguous, with one exception, possibly explained by the trade of infected plants from the same source into different locations. Multidimensional scaling corroborated this clustering and identified nursery populations as genetically most distant from the most recent outbreaks. A minimum-spanning network illustrated the evolutionary relationships among MGs, with common genotypes at the centre and singletons at the extremities; consistent with colonization by a few common genotypes followed by local evolution. Coalescent migration analyses used the original data set and a data set in which local genotypes were collapsed into common ancestral genotypes. Both analyses suggested that meta-samples 1 (Santa Cruz County) and 3 (Sonoma and Marin Counties), act as sources for most of the other forests. The untransformed data set best explains the first phases of the invasion, when the role of novel genotypes may have been minimal, whereas the second analysis best explains migration patterns in later phases of the invasion, when prevalence of novel genotypes was likely to have become more significant. Using this combined approach, we discuss possible migration routes based on our analyses, and compare them to historical and field observations from several case studies.

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