The identification and characterization of resistance genes should outpace the rapid emergence of new P. graminis f. sp. tritici races, such as TTRTF and TTKTT, to mitigate stem rust damage to wheat. The objective of the current study was to identify and characterize P. graminis f. sp. tritici race resistance association signals. A total of 250 North American spring wheat lines were evaluated at the seedling stage with a total of seven isolates including TKKTP, TKTTF, TKTTF, TRTTF, TTRTF, TTKSK, and TTKTT. The lines were genotyped by a GBS platform and 9,042 SNPs were used for identification of chromosome regions associated with resistance against the seven isolates. Strong association signals were detected on chromosomes 6BL (Sr11 gene region) and 4AL, likely Sr7a, for resistance against both TKKTP and TKTTF. Similarly, association signals were also detected on chromosomes 4AL (race TTRTF resistance) and 4BS (race TTKSK and TTKTT resistance). Association analysis based on mean phenotypic differences between closely related isolates identified QTL that were not elucidated by direct association mapping of the responses, individually. Overall, with the exception of race TRTTF, each race shared at least one association signal with another race. However, the number of race-specific association signals are larger than that of association signals common among races suggesting the need for identifying and characterizing QTL/genes for newly emerging stem rust pathogen races. There was also high concordance between PCA-based GWAS association signals and association signals from that of both single and multi-locus mixed models.
Bibliographical noteFunding Information:
Financial support was obtained from the USDA-ARS National Plant Disease Recovery System and the Delivering Genetic Gain in Wheat project administrated by Cornell University and funded by the Bill and Melinda Gates Foundation and the UK Department for International Development. GBS SNP identification was carried out on MSI High Computing cluster of University of Minnesota.
PubMed: MeSH publication types
- Journal Article
- Research Support, Non-U.S. Gov't
- Research Support, U.S. Gov't, Non-P.H.S.