Monday, November 13, 2006 - 1:30 PM

Association Mapping Applied to Wheat.

Kimberly Garland-Campbell1, Latha Reddy2, and Xianming Chen1. (1) USDA-ARS Wheat Genetics, Quality, Physiology and Disease Research Unit, 209 Johnson Hall, Box 646420, WSU, Pullman, WA 99164-6420, (2) Washington State University, Crops & Soil Science Department, 201 Johnson Hall, Pullman, WA 99164

Association mapping uses linkage disequilibrium to identify loci affecting phenotypes.  Linkage between molecular markers and traits of interest can be used to dissect and manipulate genetic control of traits of interest in breeding programs.  The objective of this talk will be to summarize recent efforts at association mapping in wheat, an allopolyploid self pollinated crop, and to describe our efforts to identify loci associated with stripe rust resistance in wheat.   Association mapping has been used by others to identify loci linked to kernel and milling quality traits, eyespot resistance, and resistance to Stagnospora blotch of wheat. Using SSRs, polymorphism rates were high enough to detect multiple alleles per marker and to detect structure in the population. Because of the polyploidy nature of the wheat genome, chromosome assignments often were confirmed using genetic stocks. Associations between markers and traits could be detected where QTLs had previously been detected.  In our study, over 300 germplasm accessions were selected from the National Small Grains Germplasm Collection for differential seedling resistance to stripe rust race 78.   Resistance reactions were confirmed in inoculated greenhouse assays and 294 accessions with stripe rust infection type scores of 1 (resistant) or 9 (susceptible) were characterized further.   To date thirty SSR markers have been genotyped on all 294 lines.  Population structure has been assessed.  The 294 accessions comprise three groups.   We are currently scoring additional molecular markers and will use mixed models analysis to detect associations between markers and stripe rust resistance.  Association mapping complements QTL analysis using single cross populations because more diversity is analyzed, population structure can be determined in the same experiment, and new sources of resistance can be identified.    As with traditional QTL analysis, marker-trait associations require validation in selection programs to fully determine their value.