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Genetic Characterization of Stem Rust Resistance in a Global Spring Wheat Germplasm Collection
Author(s) -
Gao Liangliang,
Rouse Matthew N.,
Mihalyov Paul D.,
Bulli Peter,
Pumphrey Michael O.,
Anderson James A.
Publication year - 2017
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci2017.03.0159
Subject(s) - stem rust , biology , germplasm , quantitative trait locus , puccinia , association mapping , linkage disequilibrium , plant disease resistance , genetics , agronomy , cultivar , genotype , single nucleotide polymorphism , botany , gene , mildew
Stem rust, caused by the fungus Puccinia graminis Pers. f. sp. tritici Ericks, is one of the most damaging diseases of wheat ( Triticum aestivum L.). The recent emergence of the stem rust Ug99 race group poses a serious threat to world wheat production. Utilization of genetic resistance in cultivar development is the optimal way to control stem rust. Here, we report association mapping of stem rust resistance in a global spring wheat germplasm collection (2152 accessions) genotyped with the wheat iSelect 9K single‐nucleotide polymorphism array. Using a unified mixed model method (or QK method), we identified a total of 47 loci that were significantly associated with various stem rust resistance traits including field disease resistance and seedling resistance against multiple stem rust pathogen races including BCCBC, TRTTF, TTKSK (Ug99), and TTTTF. The 47 loci could be further condensed into 11 quantitative trait locus (QTL) regions according to linkage disequilibrium information among adjacent markers. We postulate that these QTLs represent known stem rust resistance genes including Sr2 , Sr6 , Sr7a , Sr8a , Sr9h , Sr13 , Sr28 , and Sr36 . We further employed a multilocus mixed model to explore marker‐trait associations and identified two additional QTLs (one potentially represents Sr31 ) that were significantly associated with stem rust resistance against various races. Combinations of the most significant loci for each trait explained up to 38.6% of the phenotypic variance. Markers identified through this study could be used to track the genes or QTLs. Accessions with high numbers of resistance‐associated alleles may serve as important breeding materials for stem rust resistance.