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Association mapping of resistance to emerging stem rust pathogen races in spring wheat using genotyping‐by‐sequencing

Author:
Erena A. Edae, Matthew N. Rouse
Source:
The plant genome 2020 v.13 no.3 pp. e20050
ISSN:
1940-3372
Subject:
Puccinia graminis, Triticum aestivum, air temperature, chromosome mapping, chromosomes, emerging diseases, genetic resistance, genotyping by sequencing, phenotypic variation, plant disease resistance, plant pathogenic fungi, quantitative trait loci, resistance genes, seedlings, single nucleotide polymorphism, spring wheat, stem rust
Abstract:
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.
Agid:
7222915
Handle:
10113/7222915