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Differential Selection on Rhynchosporium secalis During Parasitic and Saprophytic Phases in the Barley Scald Disease Cycle

First and eighth authors: Plant Pathology, Institute of Integrative Biology, ETH Zurich, LFW, CH-8092 Zürich, Switzerlan; second, third, fourth, and sixth authors: International Center for Agricultural Research in the Dry Areas (ICARDA), P.O. Box 5466, Aleppo, Syria; fifth author: School of Botany and Zoology, The Australian National University, Bldg. 116, Daley Rd., Canberra 0200, ACT, Australia; and seventh author: Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, Scotland, U.K.

Competition among eight Rhynchosporium secalis isolates was assessed during parasitic and saprophytic phases of the disease cycle in field experiments conducted at two locations and over two growing seasons. The eight isolates were inoculated onto six barley populations exhibiting varying degrees of resistance. Microsatellite analysis of 2,866 isolates recovered from the field experiments showed significant, and sometimes opposite, changes in the frequencies of R. secalis genotypes during the growing season (parasitic phase) and between growing seasons (saprophytic phase). Isolates that showed the most complex virulence in greenhouse seedling assays had the lowest fitness in the field experiment. Significant differences in isolate fitness were found on different host populations and in different environments. Selection coefficients were large, indicating that evolution can occur rapidly in field populations. Although inoculated isolates had the lowest overall fitness on the moderately resistant landrace cv. Arabi Aswad, some isolates were more virulent and consistently increased in frequency on this landrace, suggesting a risk of directional selection and possible erosion of the resistance following its widespread deployment in monoculture. These results provide the first direct evidence that R. secalis pathogen genotypes differ in their saprophytic ability and parasitic fitness under field conditions.

Additional keywords: microsatellites, population genetics.