Genome-wide association mapping of leaf rust and stripe rust resistance in wheat accessions using the 90K SNP array

Zhang, Peipei; Yan, Xiaohui; Gebrewahid, Takele Weldu; Zhou, Yunshan; Yang, Ennian; Xia, Xianchun; He, Zhonghu; Li, Zaifeng; Liu, Daqun

doi:10.1007/s00122-021-03769-3

Cited by 51 publications

(29 citation statements)

References 58 publications

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“…The position of this common marker (562 Mbp) was quite close to previous MTA controlling seedling resistance against multi races of Pt in spring wheat (551 Mbp) which confirm our findings ( Kumar et al, 2020 ). Many Lr resistance genes were mapped on 1B chromosome such as Lr26 ( Zhang et al, 2021 ), Lr33 ( Dyck et al, 1987 ), Lr44 ( Singh et al, 2013 ), Lr46 ( Singh et al, 2013 ), Lr51 ( Helguera et al, 2005 ), Lr71 ( Singh et al, 2013 ), and Lr75 ( Singla et al, 2017 ). The near isogenic lines of four genes ( Lr26 , Lr33 , Lr44 , and Lr51 ) were available and confirmed the efficiency of only Lr51 gene against the Pt races in Exp.S.I.…”

Section: Discussionmentioning

confidence: 99%

“…To identify genomic regions controlling the target traits, genome-wide association study (GWAS) could be used. GWAS was used widely to identify marker trait associations (MTAs) with different traits in wheat including yield and traits correlated with biotic and abiotic stress resistance/tolerance ( Wang et al, 2014 , 2017 ; Sallam and Martsch, 2015 ; Sallam et al, 2017 , 2018 , 2019 ; Mourad et al, 2018a , b , 2019a , b ; Abou-Zeid and Mourad, 2021 ; Eltaher et al, 2021b ; Rollar et al, 2021 ; Zhang et al, 2021 ). It depends mainly on linkage disequilibrium between the phenotypic variation of the studied trait and molecular markers ( Alqudaha et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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Genome-Wide Screening of Broad-Spectrum Resistance to Leaf Rust (Puccinia triticina Eriks) in Spring Wheat (Triticum aestivum L.)

Mourad

Draz²,

Omar³

et al. 2022

Front. Plant Sci.

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Wheat leaf rust (LR) causes significant yield losses worldwide. In Egypt, resistant cultivars began to lose their efficiency in leaf rust resistance. Therefore, a diverse spring wheat panel was evaluated at the seedling stage to identify new sources of broad-spectrum seedling resistance against the Egyptian Puccinia triticina (Pt) races. In three different experiments, seedling evaluation was done using Pt spores collected from different fields and growing seasons. Highly significant differences were found among experiments confirming the presence of different races population in each experiment. Highly significant differences were found among the tested genotypes confirming the ability to select superior genotypes. Genome-wide association study (GWAS) was conducted for each experiment and a set of 87 markers located within 48 gene models were identified. The identified gene models were associated with disease resistance in wheat. Five gene models were identified to resist all Pt races in at least two experiments and could be identified as stable genes under Egyptian conditions. Ten genotypes from five different countries were stable against all the tested Pt races but showed different degrees of resistance.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Genome-Wide Screening of Broad-Spectrum Resistance to Leaf Rust (Puccinia triticina Eriks) in Spring Wheat (Triticum aestivum L.)

Mourad

Draz²,

Omar³

et al. 2022

Front. Plant Sci.

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“…Alternatively, genome-wide association study (GWAS) provides an effective strategy to identify associations between genotypes and phenotypes. Compared with the former, GWAS can shorten breeding years because segregation population do not need to be established, broader genetic variations can be explored, and much higher accuracy in QTL detection can be achieved ( Zhang P. et al, 2021 ). In recent years, with the development of molecular DNA markers and high-throughput genotyping technology, the single-nucleotide polymorphism (SNP) array has become a powerful tool for marker-assisted selection (MAS).…”

Section: Introductionmentioning

confidence: 99%

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Wang

Tian

et al. 2022

Front. Plant Sci.

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Kernel size and weight are crucial components of grain yield in wheat. Deciphering their genetic basis is essential for improving yield potential in wheat breeding. In this study, five kernel traits, including kernel length (KL), kernel width (KW), kernel diameter ratio (KDR), kernel perimeter (KP), and thousand-kernel weight (TKW), were evaluated in a panel consisting of 198 wheat accessions under six environments. Wheat accessions were genotyped using the 35K SNP iSelect chip array, resulting in a set of 13,228 polymorphic SNP markers that were used for genome-wide association study (GWAS). A total of 146 significant marker-trait associations (MTAs) were identified for five kernel traits on 21 chromosomes [–log10(P) ≥ 3], which explained 5.91–15.02% of the phenotypic variation. Of these, 12 stable MTAs were identified in multiple environments, and six superior alleles showed positive effects on KL, KP, and KDR. Four potential candidate genes underlying the associated SNP markers were predicted for encoding ML protein, F-box protein, ethylene-responsive transcription factor, and 1,4-α-glucan branching enzyme. These genes were strongly expressed in grain development at different growth stages. The results will provide new insights into the genetic basis of kernel traits in wheat. The associated SNP markers and predicted candidate genes will facilitate marker-assisted selection in wheat breeding.

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“…Several LD-based genome wide association studies (GWAS) for stripe rust resistance have also been conducted, leading to identification of a large number of marker trait associations (MTAs). The activity involving quantitative genetics studies for this trait increased in recent years, with at least five studies reported in 2021 3 , 29 – 32 .…”

Section: Introductionmentioning

confidence: 99%

Meta-QTLs and candidate genes for stripe rust resistance in wheat

Jan

Saripalli

Kumar

et al. 2021

Sci Rep

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In bread wheat, meta-QTL analysis was conducted using 353 QTLs that were available from earlier studies. When projected onto a dense consensus map comprising 76,753 markers, only 184 QTLs with the required information, could be utilized leading to identification of 61 MQTLs spread over 18 of the 21 chromosomes (barring 5D, 6D and 7D). The range for mean R2 (PVE %) was 1.9% to 48.1%, and that of CI was 0.02 to 11.47 cM; these CIs also carried 37 Yr genes. Using these MQTLs, 385 candidate genes (CGs) were also identified. Out of these CGs, 241 encoded known R proteins and 120 showed differential expression due to stripe rust infection at the seedling stage; the remaining 24 CGs were common in the sense that they encoded R proteins as well as showed differential expression. The proteins encoded by CGs carried the following widely known domains: NBS-LRR domain, WRKY domains, ankyrin repeat domains, sugar transport domains, etc. Thirteen breeders’ MQTLs (PVE > 20%) including four pairs of closely linked MQTLs are recommended for use in wheat molecular breeding, for future studies to understand the molecular mechanism of stripe rust resistance and for gene cloning.

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Genome-wide association mapping of leaf rust and stripe rust resistance in wheat accessions using the 90K SNP array

Cited by 51 publications

References 58 publications

Genome-Wide Screening of Broad-Spectrum Resistance to Leaf Rust (Puccinia triticina Eriks) in Spring Wheat (Triticum aestivum L.)

Genome-Wide Screening of Broad-Spectrum Resistance to Leaf Rust (Puccinia triticina Eriks) in Spring Wheat (Triticum aestivum L.)

Genome-Wide Association Study of Kernel Traits Using a 35K SNP Array in Bread Wheat (Triticum aestivum L.)

Meta-QTLs and candidate genes for stripe rust resistance in wheat

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