Variability of the stripe rust pathogen

Abstract

The stripe rust pathogen, Puccinia striiformis, is highly variable. The variation has been studied for about 100 years based on virulence, for about 30 years based on molecular markers, and for about 10 years based on genome sequencing and functional genomics. Virulence characterization using host differential genotypes has identified a large number of races or pathotypes that overcome race-specific resistance genes in cultivars of wheat and barley crops. Such information is essential for developing cultivars with effective resistance to the disease. Molecular characterization of the pathogen using various marker techniques has generated data that are useful in determination of population structure, identification of pathogen introduction and dissemination and understanding of mechanisms of variation. Molecular characterization has conducted to support findings from virulence tests and/or obtain information that is unable to produce through virulence characterization. The high variability of the stripe rust pathogen is due to its high reproductivity, capability of long-distance dissemination, and ability for adapting to various host species and environments. Among the genetic and evolutionary mechanisms for producing variation, mutation is most important in generating new races and genotypes that are under selection of host species, host cultivars and environments. The pathogen also produces new races and genotypes through somatic recombination. Sexual recombination has been recently demonstrated mainly under controlled conditions in generating variation in races and phenotypes. Natural reproduction on alternate hosts, mainly Berberis spp., has been so far found in China, but its role in generating aeciospores to start stripe rust epidemics on cereal crops and creating new races to attack crop cultivars is still unclear in this country, while ruled out in some other countries. Compared to other fungal pathogens, research on genome sequencing and functional genomics has started relatively late, but recent studies have generated huge data that have helped in understanding the pathogen variation and created useful resources for developing new tools for further studying and monitoring the pathogen variation.