Genomic regions conferring resistance to multiple fungal pathogens in synthetic hexaploid wheat

Jighly, Abdulqader; Manickavelu, Alagu; Makdis, Farid; Singh, Murari; Singh, Sukhwinder; Emebiri, Livinus; Ogbonnaya, Francis C.

doi:10.1007/s11032-016-0541-4

Cited by 52 publications

(56 citation statements)

References 107 publications

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“…This QTL contributed by the Begra allele is delimited by markers Xgdm46 and Xwmc157, localized at positions 183.1 cM and 234.3 cM, respectively, on the high resolution wheat consensus map (Quraishi et al 2017). This chromosome was reported to contain two QTL for SNG resistance in a genome-wide association study (GWAS) on a set of synthetic hexaploid wheat (Jighly et al 2016) mapped at a position close to 35 cM and 125 cM, respectively, based on comparative analysis of a high resolution wheat consensus map (Quraishi et al 2017) and consensus map of wheat v. 4.0 (Diversity Arrays Technology 2018). Therefore, QSnl.ihar-7D detected in our study resides at a different position on chromosome 7D compared to those reported by Jighly et al (2016).…”

Section: Discussionmentioning

confidence: 99%

“…Molecular mapping and quantitative trait loci (QTL) analyses using bi-parental populations and genome-wide association studies (GWAS) greatly augment the understanding of the inheritance and genetic control of SNB resistance. A number of QTL have been identified on chromosomes such as 1A, 1B, 2B, 2D, 3A, 4A, 4B, 4D, 5A, 5B, 5D, 6A, 6D, 7A, 7B and 7D for the seedling resistance (Czembor et al 2003;Arseniuk et al 2004;Liu et al 2004b;Reszka et al 2007;Shankar et al 2008;Faris and Friesen 2009;Friesen et al 2009Friesen et al , 2012Adhikari et al 2011;Abeysekara et al 2012;Ruud et al 2017;Phan et al 2018), on 1A, 1B, 2A, 2D, 3A, 3B, 4B, 5A, 5B, 7B and 7A for adult plant leaf resistance (Aguilar et al 2005;Shankar et al 2008;Friesen et al 2009;Francki et al 2011;Lu and Lillemo 2014;Jighly et al 2016;Ruud et al 2017;Francki et al 2018), and on 2A, 2B, 2D, 3A, 3B, 4A, 4B, 5A, 5B, 6B, 7A and 7D for glume resistance (Schnurbusch et al 2003;Aguilar et al 2005;Uphaus et al 2007;Shankar et al 2008;Shatalina et al 2014;Jighly et al 2016;Francki et al 2018).…”

Section: Introductionmentioning

confidence: 99%

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Quantitative trait loci analysis of adult plant resistance to Parastagonospora nodorum blotch in winter wheat cv. Liwilla (Triticum aestivum L.)

et al. 2019

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Parastagonospora nodorum leaf and glume blotch (syn. Septoria nodorum blotch, SNB) is a severe disease in many wheat-growing areas worldwide. In a previous study, a mapping population, Liwilla × Begra, was used to detect several resistance quantitative trait loci (QTL) at the seedling stage. In this study the same mapping population was analysed at the adult plant stage under field and polytunnel conditions. After artificial inoculation the disease severity on leaves and glumes was scored as the areas under the disease progress curves for field tests and as the percentage of the leaf and glume area covered by necrosis for the polytunnel test. Three QTL associated with Septoria nodorum glume blotch resistance and two QTL associated with Septoria nodorum leaf blotch resistance were detected on chromosomes 1B, 3A, 4A and 7D. Each of the detected QTL explained only a small proportion of the total phenotypic variation, ranging from 9.1 to 20.0%. None of these QTL co-located with necrotrophic effector sensitivity loci or aligned with previously identified resistance loci at the seedling stage for the Liwilla × Begra population. SNB resistance QTL detected in our study did not overlap with QTL associated with morphological and developmental traits. Therefore they could be involved in the defence reaction and can be considered in wheat improvement for SNB resistance.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Quantitative trait loci analysis of adult plant resistance to Parastagonospora nodorum blotch in winter wheat cv. Liwilla (Triticum aestivum L.)

et al. 2019

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“…Similar to migration effect in diploids, speciation also leads to larger LD blocks and higher relatedness (Ardlie et al., ) (Supporting Information Tables S1 and S2). Although it is unlikely that such high geneflow rates are observed in nature, for example, the 0.01 simulated here, similarly high gene flow has been induced in laboratories for many allopolyploids such as wheat (e.g., Jighly, Joukhadar, Singh, & Ogbonnaya, ; Jighly et al., ) and autopolyploids such as potato (Stupar et al., ) to introduce new variation to the breeding populations. PolySim allows for additional gene flow during the expansion of newly emerged polyploid populations, which had not been tested previously.…”

Section: Discussionmentioning

confidence: 72%

Insights into population genetics and evolution of polyploids and their ancestors

Jighly

Lin

Forster

et al. 2018

Molecular Ecology Resources

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We have developed the first comprehensive simulator for polyploid genomes (PolySim) and demonstrated its value by performing large-scale simulations to examine the effect of different population parameters on the evolution of polyploids. PolySim is unlimited in terms of ploidy, population size or number of simulated loci. Our process considered the evolution of polyploids from diploid ancestors, polysomic inheritance, inbreeding, recombination rate change in polyploids and gene flow from lower to higher ploidies. We compared the number of segregating single nucleotide polymorphisms, minor allele frequency, heterozygosity, R and average kinship relatedness between different simulated scenarios, and to real data from polyploid species. As expected, allotetraploid populations showed no difference from their ancestral diploids when population size remained constant and there was no gene flow or multivalent (MV) pairing between subgenomes. Autotetraploid populations showed significant differences from their ancestors for most parameters and diverged from their ancestral populations faster than allotetraploids. Autotetraploids can have significantly higher heterozygosity, relatedness and extended linkage disequilibrium compared with allotetraploids. Interestingly, autotetraploids were more sensitive to increasing selfing rate and decreasing population size. MV formation can homogenize allotetraploid subgenomes, but this homogenization requires a higher MV rate than previously proposed. Our results can be considered as the first building block to understand polyploid population evolutionary dynamics. PolySim can be used to simulate a wide variety of polyploid organisms that mimic empirical populations, which, in combination with quantitative genetics tools, can be used to investigate the power of genomewide association, genomic selection or breeding programme designs in these species.

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“…This platform uses genome complexity reduction and the next-generation sequencing (NGS) of short DNA fragments on the Illumina platform [19,20]. The DArTseq™ technique has been applied for genotyping by sequencing [20][21][22], linkage mapping, QTL identification [23,24], GWAS (genome-wide association studies), MAS (marker-assisted selection), and GS (genomic selection) [25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Identification and mapping of a new recessive dwarfing gene dw9 on the 6RL rye chromosome and its phenotypic effects

et al. 2020

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The introduction of high-yielding semi-dwarf varieties of wheat into cultivation has led to a "green revolution." This has required intensive research into various sources of dwarfism in wheat. However, there has been very little advancement in research on dwarfing genes in rye in comparison to wheat or barley. So far, three dominant dwarfing genes (Ddw1, Ddw3, and Ddw4) and three recessive genes (ct1, ct2, and np) have been characterized and precisely mapped in rye. There is no complete catalog of dwarfing genes available in rye. This paper presents an identification of the source of dwarfism and preliminary characterization of the new recessive gene dw9 from the BK-1 line. The gene was mapped on the long arm of the 6R chromosome and belongs to the GA-insensitive group. The initial characterization of the influence of this gene on morphological traits shows that it significantly affects the decrease of yielding trait parameters. A full evaluation can be performed after detailed breeding studies.

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Genomic regions conferring resistance to multiple fungal pathogens in synthetic hexaploid wheat

Cited by 52 publications

References 107 publications

Quantitative trait loci analysis of adult plant resistance to Parastagonospora nodorum blotch in winter wheat cv. Liwilla (Triticum aestivum L.)

Quantitative trait loci analysis of adult plant resistance to Parastagonospora nodorum blotch in winter wheat cv. Liwilla (Triticum aestivum L.)

Insights into population genetics and evolution of polyploids and their ancestors

Identification and mapping of a new recessive dwarfing gene dw9 on the 6RL rye chromosome and its phenotypic effects

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