Pathogenic variability in Pyricularia grisea at a rice blast "hot spot" breeding site in Eastern Colombia
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Permanent link to this item: http://hdl.handle.net/10568/43929
Forty-five international races of Pyricularia grisea, representing all nine race groups, were identified in a "hot spot" breeding site (Santa Rosa) in Colombia, with the largest number included in the IA group. The international race system did not fully describe the virulence spectrum of the isolates, since several races could be further differentiated into different pathotypes when local commercial cultivars were used as differentials. Compatibility was present in the pathogen population for at least 13 known resistance genes and resistance sources tested. Frequency of virulent phenotypes on the 42 cultivars tested ranged from 0.0 to 0.86, with no cultivar susceptible to all isolates. The lowest compatibility frequencies were associated with combinations of resistance genes. It was unusual to recover isolates compatible with cultivars K-8, Peta, Ceysvoni, IR-42, Fujisaka 5, Fukunishiki, Zenith, and NP-125. No isolates were recovered that were compatible with the newly released cultivars Oryzica Llanos 4 and 5 developed at this site, and very few infected CICA 9. Analysis of the compatibility frequency of isolates recovered from commercial rice cultivars revealed a marked specialization for cultivar origin. Some cultivars were infected mainly by isolates recovered from the same cultivar. Virulence factors were accumulated in the most virulent isolates, but no isolate was virulent to all rice cultivars. Regardless, matching virulence for all resistance genes is already present in the pathogen population, indicating that new combinations of resistance factors and/or new resistance genes are needed. Rare compatibility with particular cultivars suggests that combinations of certain virulence genes may be associated with poor fitness. Differences in the distribution of virulence genes of P. grisea among and within cultivars support the feasibility of gene deployment strategies.