Genomic analysis,trajectory tracking,and field surveys reveal sources and long-distance dispersal routes of wheat stripe rust pathogen in China

Identifying sources of phytopathogen inoculum and determining their contributions to disease outbreaks are essential for predicting disease development and establishing control strategies.Puccinia striiformis f.sp.tritici(Pst),the causal agent of wheat stripe rust,is an airborne fungal pathogen with rapid virulence variation that threatens wheat production through its long-distance migration.Because of wide variation in geographic features,climatic conditions,and wheat production systems,Pst sources and related dispersal routes in China are largely unclear.In the present study,we performed genomic analyses of 154 Pst isolates from all major wheat-growing regions in China to determine Pst population structure and diversity.Through trajectory tracking,historical migration studies,genetic introgression analyses,and field surveys,we investigated Pst sources and their contributions to wheat stripe rust epidemics.We identified Longnan,the Himalayan region,and the Guizhou Plateau,which contain the highest population genetic diversities,as the Pst sources in China.Pst from Longnan disseminates mainly to eastern Liupan Mountain,the Sichuan Basin,and eastern Qinghai;that from the Himalayan region spreads mainly to the Sichuan Basin and eastern Qinghai;and that from the Guizhou Plateau migrates mainly to the Sichuan Basin and the Central Plain.These findings improve our current understanding of wheat stripe rust epidemics in China and emphasize the need for managing stripe rust on a national scale.

Modeling of the overwintering distribution of Puccinia striiformis f.sp.tritici based on meteorological data from 2001 to 2012 in China

Wheat stripe rust caused by Puccinia striiformis f.sp.tritici occurs widely in China and seriously affects wheat production.Global warming could profoundly impact the incidence and prevalence of lowtemperature diseases such as stripe rust.Studies on the effects of temperature on the distribution of overwintering stripe rust could help us understand the incidence and prevalence of the disease and could also provide support for monitoring,forecasting and developing control strategies.An exponential model and a spherical model of the ordinary Kriging method in the ArcGIS platform were used to predict the overwintering regions of stripe rust based on the probability that the average temperature of the coldest month from December to February was higher than–6 or–7°C from 2001 to 2012.The results showed that the areas with a probability between 70%and 90%were transition regions for the overwintering of stripe rust.Based on annual mean temperature of the coldest month from December to February for 2001 to 2012,overwintering distribution of stripe rust was likewise evaluated.The boundary for overwintering of stripe rust was consistent with the areas where the probability was predicted to be 70%to 90%for the overwintering distribution of stripe rust,but the boundary was shifted northward toward Beijing in North China.Some areas in Xinjiang,including Akto,Pishan,Hotan and Yutian,were also predicted to be suitable for the overwintering of stripe rust.