Abstract
Key message
Co-localization of a major QTL for wheat stripe rust resistance to a 3.9-cM interval on chromosome 6BL across both populations and another QTL on chromosome 2B with epistatic interaction.
Abstract
Cultivars with diverse resistance are the optimal strategy to minimize yield losses caused by wheat stripe rust (Puccinia striiformis f. sp. tritici). Two wheat populations involving resistant wheat lines P10078 and Snb“S” from CIMMYT were evaluated for stripe rust response in multiple environments. Pool analysis by Wheat660K SNP array showed that the overlapping interval on chromosome 6B likely harbored a major QTL between two populations. Then, linkage maps were constructed using KASP markers, and a co-localized locus with large effect on chromosome 6BL was detected using QTL analysis in both populations. The coincident QTL, named QYr.nwafu-6BL.2, explained 59.7% of the phenotypic maximum variation in the Mingxian 169 × P10078 and 52.5% in the Zhengmai 9023 × Snb“S” populations, respectively. This co-localization interval spanning 3.9 cM corresponds to ~ 30.5-Mb genomic region of the newest common wheat reference genome (IWGSC RefSeq v.1.0). In addition, another QTL was also detected on chromosome 2B in Zhengmai 9023 × Snb“S” population and it can accelerate expression of QYr.nwafu-6BL.2 to enhance resistance with epistatic interaction. Allowing for Pst response, marker genotypes, pedigree analysis and relative genetic distance, QYr.nwafu-6BL.2 is likely to be a distinct adult plant resistance QTL. Haplotype analysis of QYr.nwafu-6BL.2 revealed specific SNPs or alleles in the target region from a diversity panel of 176 unrelated wheat accessions. This QTL region provides opportunity for further map-based cloning, and haplotypes analysis enables pyramiding favorable alleles into commercial cultivars by marker-assisted selection.
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Acknowledgements
The authors are grateful to Prof. R. A. McIntosh, Plant Breeding Institute, University of Sydney, for review of this manuscript. Dr. Jianhui Wu thanks Mr Yue Liu for participating in making the figures. This study was financially supported by the National Science Foundation for Young Scientists in China (Grant 31701421), the Genetically Modified Organisms Breeding Major Project (2016ZX08002001), and the earmarked fund for Modern Agro-industry Technology Research System (No. CARS-3-1-11).
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Table S1
. Genotypic data and stripe rust responses assessed by infection type (IT) and disease severity (DS) on the Mingxian 169 × P10078 RIL population (Table A) and Zhengmai 9023 × Snb“S” F2:3 lines (Table B) recorded at indicated dates at Yangling and Jiangyou during 2016–2017 (XLSX 126 kb)
Table S2.
Number of SNPs per megabase in different chromosomes from RIL (Table A) and F2:3 (Table B) bulks. (XLSX 64 kb)
Table S3.
Kompetitive allele specific PCR (KASP) primers used to genotype individual F2 plants and RILs for mapping stripe rust resistance loci in P10078 and Snb“S” (XLSX 12 kb)
Table S4.
The physical positions of EST in different sets of chromosome 2B (Table A) and 6B (Table B) bins (XLSX 46 kb)
Table A in S5.
Numbers of Mingxian 169 × P10078 RILs for resistance locus QYr.nwafu-6BL.2, showing mean stripe rust severities (%), when the resistance QTL was absent or present. Table B in S5. Effects of different combinations on number of QTL in combination in the F2:3 lines in the Zhengmai 9023 × Snb“S” population based on mean DS and IT in four field experiments (XLSX 30 kb)
Table S6.
Phenotypes and alleles of SNP markers flanking QYr.nwafu-6BL.2 and QYrsnb.nwafu-2BL in 176 wheat accessions including parents, donors of reported Yr genes/QTL on 6BL, susceptible checks, cultivars and advanced breeding lines (XLSX 47 kb)
Table S7.
Gene models between flanking markers AX-109585549 and AX-110989911 (positions 593,965,904 and 624,478,659, respectively, on chromosome 6B according to the Chinese Spring IWGSC RefSeq v1.0) (XLSX 38 kb)
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Zeng, Q., Wu, J., Liu, S. et al. A major QTL co-localized on chromosome 6BL and its epistatic interaction for enhanced wheat stripe rust resistance. Theor Appl Genet 132, 1409–1424 (2019). https://doi.org/10.1007/s00122-019-03288-2
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DOI: https://doi.org/10.1007/s00122-019-03288-2