Genetic Diversity, Linkage Disequilibrium, and Genome Evolution in Soft Winter Wheat

Cabrera, Antonio G.; Souza, E. M. R.; Guttieri, Mary J.; Sturbaum, Anne; Hoffstetter, Amber; Sneller, Clay

doi:10.2135/cropsci2013.09.0601

Cited by 13 publications

(24 citation statements)

References 60 publications

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“…Results from association analysis using both models (Q + K and PCs + K) were very consistent despite showing small differences in the significant level, therefore we report on the results from Q + K model as it most likely represent better the population structure previously described for this population (Cabrera et al 2014). In our association analysis of 583 DArTs and 10 gene-based markers, significant associations at family-wise significant level or false discovery rate (FDR) were not detected.…”

Section: Association Analysis In a Diversity Panelsupporting

confidence: 56%

“…We integrated the mapping of quality traits in a diversity panel of 187 lines selected as described by Souza et al (2012) and characterized by Cabrera et al (2014); and five soft red winter wheat (SRWW) bi-parental populations ( Table 1). The results obtained were compared to published results (Smith et al 2011).…”

Section: Populationsmentioning

confidence: 99%

“…The K matrix (kinship matrix) was used as the random term, while population structure was fitted using two methods: the Q matrix (Pritchard et al 2000) from the most likely number of subpopulations previously reported for this population (Cabrera et al 2014) and principal components (PCs). The K matrix (kinship matrix) was used as the random term, while population structure was fitted using two methods: the Q matrix (Pritchard et al 2000) from the most likely number of subpopulations previously reported for this population (Cabrera et al 2014) and principal components (PCs).…”

Section: Genotyping and Mappingmentioning

confidence: 99%

“…The significant regions were defined as in Cabrera et al (2014). Genotyping score of 1 and 0 was used to represent the presence Y = Xβ + Zu + ε and absence for the 1BL.1RS and 1AL.1RS translocations (detected by marker XScm9), for the Hap-H and Hap-L alleles (detected by the KASP marker RSGGL for Sucrose synthase gene Sus2), for the dwarf alleles (Rht1 from Rht-B1b and Rht2 from Rht-D1b), for the photoperiod insensitivity alleles (Ppd-D1a from Ppd-D1 and Ppd-B1a from Ppd-B1) and for the gluten strength alleles GluD1-Dx2, GluD1-Dx5, GluB1-By8, GluB1-By9 and GluB1-B16 from gluten strength genes GluD1 and GluB1.…”

Section: Genotyping and Mappingmentioning

confidence: 99%

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Identification of milling and baking quality QTL in multiple soft wheat mapping populations

Cabrera

Guttieri

Smith³

et al. 2015

Theor Appl Genet

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Two mapping approaches were use to identify and validate milling and baking quality QTL in soft wheat. Two LG were consistently found important for multiple traits and we recommend the use marker-assisted selection on specific markers reported here. Wheat-derived food products require a range of characteristics. Identification and understanding of the genetic components controlling end-use quality of wheat is important for crop improvement. We assessed the underlying genetics controlling specific milling and baking quality parameters of soft wheat including flour yield, softness equivalent, flour protein, sucrose, sodium carbonate, water absorption and lactic acid, solvent retention capacities in a diversity panel and five bi-parental mapping populations. The populations were genotyped with SSR and DArT markers, with markers specific for the 1BL.1RS translocation and sucrose synthase gene. Association analysis and composite interval mapping were performed to identify quantitative trait loci (QTL). High heritability was observed for each of the traits evaluated, trait correlations were consistent over populations, and transgressive segregants were common in all bi-parental populations. A total of 26 regions were identified as potential QTL in the diversity panel and 74 QTL were identified across all five bi-parental mapping populations. Collinearity of QTL from chromosomes 1B and 2B was observed across mapping populations and was consistent with results from the association analysis in the diversity panel. Multiple regression analysis showed the importance of the two 1B and 2B regions and marker-assisted selection for the favorable alleles at these regions should improve quality.

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Section: Association Analysis In a Diversity Panelsupporting

confidence: 56%

Section: Populationsmentioning

confidence: 99%

Section: Genotyping and Mappingmentioning

confidence: 99%

Section: Genotyping and Mappingmentioning

confidence: 99%

See 2 more Smart Citations

Identification of milling and baking quality QTL in multiple soft wheat mapping populations

Cabrera

Guttieri

Smith³

et al. 2015

Theor Appl Genet

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“…The population contained multiple lines from the same cross and full sibs and half sibs clustered together. When the structure of this population was analyzed by Cabrera et al (2014), population stratification suggested up to six groups. The six groups were mainly distinguished based on differential parentage from the following key parents: VA98W‐706, P.961341A3‐2‐2, P.92145E8‐7‐7‐1‐9, ‘Roane’, ‘Patton’, ‘Honey’, and OH751 (Cabrera et al, 2014).…”

Section: Resultsmentioning

confidence: 99%

Identifying Quantitative Trait Loci for Economic Traits in an Elite Soft Red Winter Wheat Population

Hoffstetter¹,

Cabrera²,

Sneller³

2016

Crop Science

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Genotyping‐by‐sequencing (GBS), reduces genotyping costs and allows breeders to genotype large populations with thousands of markers. Genome‐wide association studies with GBS markers can be used to identify quantitative trait loci (QTL) for important traits in elite populations of soft red winter wheat (SRWW; Triticum aestivum L.). Our objective was to identify potential QTL for grain yield (GY), Fusarium head blight resistance (FHB), flour yield (FY), and softness equivalence (SE) in a set of 470 elite SWRR wheat lines that were genotyped with 33,169 GBS markers and phenotyped in multiple environments. For all traits, we found lines that were phenotypically superior to the elite checks. We identified four FHB QTL, nine QTL for quality, and 14 QTL for with R2 values ranging from 1.6 to 3.5%. The QTL with the largest effect for FHB resistance reduced disease by 1.76%. For quality, the largest‐effect QTL increased FY and SE by 0.37 and 0.67%, respectively. For GY the QTL with the largest effect in Wooster, OH, increased GY by 129.6 kg ha−1, for northwest Ohio, the largest‐effect QTL increased GY by 67.2 kg ha−1, and the largest‐effect QTL for GY over all environments increased GY by 48.8 kg ha−1. While marker‐assisted selection (MAS) for these QTL could be used to improve these traits, the preponderance of genetic variation appeared to be controlled by genes with small effect, suggesting that MAS should be used as a supplement to genomic selection.

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The effects of crop attributes, selection, and recombination on Canadian bread wheat molecular variation

Hargreaves

N’Daiye

Walkowiak³

et al. 2021

The Plant Genome

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Cultivated germplasm provides an opportunity to investigate how crop agronomic traits, selection for major genes, and differences in crossing-over rates drive patterns of allelic variation. To identify how these factors correlated with allelic variation within a collection of cultivated bread wheat (Triticum aestivum L.), we generated genotypes for 388 accessions grown in Canada over the past 170 yr using filtered single nucleotide polymorphism (SNP) calls from an Illumina Wheat iSelect 90K SNP-array. Entries' breeding program, era of release, grain texture, kernel color, and growth habit contributed to allelic differentiation. Allelic diversity and linkage disequilibrium (LD) of markers flanking some major loci known to affect traits such as gluten strength, growth habit, and grain color were consistent with selective sweeps. Nonetheless, some flanking markers of major loci had low LD and high allelic diversity. Positive selection may have acted upon homoeologous genes that had significant enrichment for the gene ontology terms 'response-to-auxin' and 'response-to-wounding.' Long regions of LD, spanning approximately one-third the length of entire chromosomes, were associated with many pericentromeric regions. These regions were also characterized by low diversity. Enhancing recombination across these regions could generate novel allele combinations to accelerate Canadian wheat improvement.

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Genetic Diversity, Linkage Disequilibrium, and Genome Evolution in Soft Winter Wheat

Cited by 13 publications

References 60 publications

Identification of milling and baking quality QTL in multiple soft wheat mapping populations

Identification of milling and baking quality QTL in multiple soft wheat mapping populations

Identifying Quantitative Trait Loci for Economic Traits in an Elite Soft Red Winter Wheat Population

The effects of crop attributes, selection, and recombination on Canadian bread wheat molecular variation

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