Identification of genomic regions conferring rust resistance and enhanced mineral accumulation in a HarvestPlus Association Mapping Panel of wheat

2022 ◽  
Author(s):  
Deepak Baranwal ◽  
Suong Cu ◽  
James Stangoulis ◽  
Richard Trethowan ◽  
Harbans Bariana ◽  
...  
Keyword(s):  
Association Mapping ◽  
Rust Resistance ◽  
Mapping Panel ◽  
Genomic Regions ◽  
Mineral Accumulation

scholarly journals A framework for gene mapping in wheat demonstrated using the Yr7 yellow rust resistance gene

2019 ◽  
Author(s):  
Laura-Jayne Gardiner ◽  
Pauline Bansept-Basler ◽  
Mohamed El-Soda ◽  
Anthony Hall ◽  
Donal M. O’Sullivan
Keyword(s):  
Association Mapping ◽  
Candidate Gene ◽  
Resistance Gene ◽  
Rust Resistance ◽  
Yellow Rust ◽  
Snp Array ◽  
Rust Resistance Gene ◽  
Mapping Panel ◽  
Yellow Rust Resistance ◽  
Mapping By Sequencing

AbstractWe used three approaches to map the yellow rust resistance gene Yr7 and identify associated SNPs in wheat. First, we used a traditional QTL mapping approach using a double haploid (DH) population and mapped Yr7 to a low-recombination region of chromosome 2B. To fine map the QTL, we then used an association mapping panel. Both populations were SNP array genotyped allowing alignment of QTL and genome-wide association scans based on common segregating SNPs. Analysis of the association panel spanning the QTL interval, narrowed the interval down to a single haplotype block. Finally, we used mapping-by-sequencing of resistant and susceptible DH bulks to identify a candidate gene in the interval showing high homology to a previously suggested Yr7 candidate and to populate the Yr7 interval with a higher density of polymorphisms. We highlight the power of combining mapping-by-sequencing, delivering a complete list of gene-based segregating polymorphisms in the interval with the high recombination, low LD precision of the association mapping panel. Our mapping-by-sequencing methodology is applicable to any trait and our results validate the approach in wheat, where with a near complete reference genome sequence, we are able to define a small interval containing the causative gene.HighlightWe show progression from genetic mapping to mapping-by-sequencing and the overlap of defined intervals by each approach culminating with interval refinement and identification of a candidate gene for disease resistance.

scholarly journals Dissection of the genetic basis of oil content in Chinese peanut cultivars through association mapping

2020 ◽  
Author(s):  
Nian Liu ◽  
Li Huang ◽  
Weigang Chen ◽  
Bei Wu ◽  
Manish K. Pandey ◽  
...  
Keyword(s):  
Association Mapping ◽  
Ssr Markers ◽  
Oil Content ◽  
Genetic Basis ◽  
Principal Component ◽  
Primary Sources ◽  
Phenotypic Variance ◽  
Mapping Panel ◽  
Stable Association ◽  
Faster Development

Abstract Background: Peanut is one of the primary sources for vegetable oil worldwide, and enhancing oil content is the main objective in several peanut breeding programs of the world. Tightly linked markers are required for faster development of high oil content peanut varieties through genomics-assisted breeding (GAB), and association mapping is one of the promising approaches for discovery of such associated markers. Results: An association mapping panel consisting of 292 peanut varieties extensively distributed in China was phenotyped for oil content and genotyped with 583 polymorphic SSR markers. These markers amplified 3663 alleles with an average of 6.28 alleles per locus. The structure, phylogenetic relationship, and principal component analysis (PCA) indicated two subgroups majorly differentiating based on geographic regions. Genome-wide association analysis identified 12 associated markers including one (AGGS1014_2) highly stable association controlling up to 9.94% phenotypic variance explained (PVE) across multiple environments. Interestingly, the frequency of the favorable alleles for 12 associated markers showed a geographic difference. Two associated markers (AGGS1014_2 and AHGS0798) with 6.90-9.94% PVE were verified to enhance oil content in an independent RIL population and also indicated selection during the breeding program. Conclusion: This study provided insights into the genetic basis of oil content in peanut and verified highly associated two SSR markers to facilitate marker-assisted selection for developing high-oil content breeding peanut varieties.

Comparative mapping of the two wheat leaf rust resistance loci Lr1 and Lr10 in rice and barley

Genome ◽  
1998 ◽  
Vol 41 (3) ◽  
pp. 328-336 ◽  
Author(s):  
Francesca Gallego ◽  
Catherine Feuillet ◽  
Monika Messmer ◽  
Anja Penger ◽  
Andreas Graner ◽  
...  
Keyword(s):  
Leaf Rust ◽  
Comparative Mapping ◽  
Rust Resistance ◽  
Repetitive Sequences ◽  
Rice Chromosome ◽  
Leaf Rust Resistance ◽  
Chromosome 1 ◽  
Wheat Leaf Rust ◽  
Wheat Leaf ◽  
Genomic Regions

The wheat genome is large, hexaploid, and contains a high amount of repetitive sequences. In order to isolate agronomically important genes from wheat by map-based cloning, a simpler model of the genome must be used for identifying candidate genes. The objective of this study was to comparatively map the genomic regions of two wheat leaf rust disease resistance loci, Lr1 and Lr10, in the putative model genomes of rice and barley. Two probes cosegregating with the Lr1 gene on chromosome 5DL of wheat were studied. The rice sequences corresponding to the two probes were isolated and mapped. The two probes mapped to two different rice chromosomes, indicating that the organization of the region orthologous to Lr1 is different in rice and wheat. In contrast, synteny was conserved between wheat and barley in this chromosomal region. The Lrk10 gene cosegregated with Lr10 on chromosome 1AS in wheat. The rice gene corresponding to Lrk10 was mapped on rice chromosome 1, where it occurred in many copies. This region on rice chromosome 1 corresponds to the distal part of the group 3S chromosomes in Triticeae. The synteny is conserved between rice chromosome 1 and the Triticeae group 3S chromosomes up to the telomere of the chromosomes. On group 3S chromosomes, we found a gene that is partially homologous to Lrk10. We conclude that in the genomic regions studied, there is limited and only partially useful synteny between wheat and rice. Therefore, barley should also be considered as a model genome for isolating the Lr1 and Lr10 genes from wheat.Key words: barley, comparative mapping, leaf rust, resistance genes, rice, synteny, wheat.

Association mapping and gene–gene interaction for stem rust resistance in CIMMYT spring wheat germplasm

2011 ◽  
Vol 123 (8) ◽  
pp. 1257-1268 ◽  
Author(s):  
Long-Xi Yu ◽  
Aaron Lorenz ◽  
Jessica Rutkoski ◽  
Ravi P. Singh ◽  
Sridhar Bhavani ◽  
...  
Keyword(s):  
Association Mapping ◽  
Spring Wheat ◽  
Stem Rust ◽  
Rust Resistance ◽  
Gene Interaction ◽  
Stem Rust Resistance ◽  
Wheat Germplasm

Genome-wide association mapping of genomic regions associated with phenotypic traits in Canadian western spring wheat

2017 ◽  
Vol 37 (11) ◽  
Author(s):  
Hua Chen ◽  
Kassa Semagn ◽  
Muhammad Iqbal ◽  
Neshat Pazooki Moakhar ◽  
Teketel Haile ◽  
...  
Keyword(s):  
Association Mapping ◽  
Spring Wheat ◽  
Genome Wide Association ◽  
Phenotypic Traits ◽  
Genome Wide ◽  
Genomic Regions

scholarly journals Genome-Wide Association Mapping of Stem Rust Resistance inHordeum vulgaresubsp.spontaneum

2017 ◽  
Vol 7 (10) ◽  
pp. 3491-3507 ◽  
Author(s):  
Ahmad H. Sallam ◽  
Priyanka Tyagi ◽  
Gina Brown-Guedira ◽  
Gary J. Muehlbauer ◽  
Alex Hulse ◽  
...  
Keyword(s):  
Association Mapping ◽  
Stem Rust ◽  
Rust Resistance ◽  
Stem Rust Resistance ◽  
Genome Wide Association ◽  
Genome Wide

scholarly journals Genetic analysis and characterization of a new maize association mapping panel for quantitative trait loci dissection

2010 ◽  
Vol 121 (3) ◽  
pp. 417-431 ◽  
Author(s):  
Xiaohong Yang ◽  
Jianbing Yan ◽  
Trushar Shah ◽  
Marilyn L. Warburton ◽  
Qing Li ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Genetic Analysis ◽  
Association Mapping ◽  
Quantitative Trait ◽  
Mapping Panel ◽  
Trait Loci

scholarly journals Genomic regions underlying agronomic traits in linseed ( Linum usitatissimum L.) as revealed by association mapping

2014 ◽  
Vol 56 (1) ◽  
pp. 75-87 ◽  
Author(s):  
Braulio J. Soto‐Cerda ◽  
Scott Duguid ◽  
Helen Booker ◽  
Gordon Rowland ◽  
Axel Diederichsen ◽  
...  
Keyword(s):  
Association Mapping ◽  
Linum Usitatissimum ◽  
Agronomic Traits ◽  
Linum Usitatissimum L ◽  
Genomic Regions
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