条锈病是严重威胁小麦安全生产的重大流行性病害，云南是条锈病的重发区，是我国条锈菌能顺利越夏越冬及毒性最复杂的少数地区之一，云南具有初菌源地的重要特征及远距离传播的必备条件，在回答云南小麦条锈菌与其它流行区的关系之前，系统认识其群体结构，迫切重要，这是揭示其起源、进化及传播最有效的途径。单核苷酸多态性（SNP）是基于DNA序列的新一代多位点种群分析技术，在真菌基因组中发生频率高，易检测到，其精度和可靠性较DNA指纹技术高且省时，已逐渐用于植物病原真菌起源、进化及基因漂移等研究，并在美国成功用于小麦白粉菌群体遗传研究。看家基因由于在所有细胞中能稳定表达，本项目首次采用小麦条锈菌看家基因NCS1、MAPK1、β-tublin1、Cdc2和秆锈菌看家基因Ef-1α等SNP解析云南小麦条锈菌群体遗传结构，深入揭示其起源、进化及传播。同时辅以病菌毒性的时空演化及病情发生的时间序列予以印证。

Wheat stripe (yellow) rust is one of the most important epidemics which threaten wheat security severely. Yunnan is a district where stripe rust breaks out constantly, it is one of the fewer regions in China where the pathogen can over summer and winter and the pathogen is very complex. Yunnan has the important characteristics of original pathogen base of stripe rust and prerequisite of pathogen migrating for long distance. It's very important to know the population genetic structure of stripe rust pathogen in Yunnan before answering the relationship of pathogen between Yunnan and other epidemic regions, because it is the most effective method to reveal the origin, evolution and migration of pathogen. Single neucleotide polymorphism (SNP) is a new technique of multilocus population analysis based on DNA sequence.It has a high frequency in fungi genome and can be detected easily, and has higher precision and reliability than DNA fingerprint and spend little time. SNP has been used for researching the origin, evolution and gene flow of plant pathogen gradually and has succeeded in population genetic research of powdery mildew pathogen in America. Because house-keeping genes can express stably in all of cells,so this project we will analyse the population genetic structure of stripe rust pathogen in Yunnan by SNP of house-keeping genes such as NCS1, MAPK1, β-tublin1, Cdc2 of Puccinia striformis f.sp. tritici and Ef-1α of Puccinia graminis f.sp. tritici for the first time, to reveal the origin, evolution and migration of Puccinia striformis f.sp. tritici deeply. And confirm the results by pathogen virulence evolution in space and time and disease occurred time order in fields.