QTL for quality parameters for bread-making in a segregating wheat by spelt population

Zanetti, S.; Keller, Martin; Winzeler, M.; Saurer, W.; Keller, Beat; Messmer, Monika

doi:10.1007/978-94-011-4475-9_40

Cited by 7 publications

(7 citation statements)

References 3 publications

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“…The ZSVs (means ± SD) of the eight recombinant genotypes showed continuous variation (Table 3), consistent with previous findings showing that ZSV is controlled quantitatively by multiple chromosomal loci located on different wheat chromosomes [34], [65], [66]. Nevertheless, our statistical analysis showed that the averaged ZSV of A3 x B3 x D3 x was significantly higher than that of A3 j B3 j D3 j .…”

Section: Resultssupporting

confidence: 90%

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New Insights into the Organization, Recombination, Expression and Functional Mechanism of Low Molecular Weight Glutenin Subunit Genes in Bread Wheat

et al. 2010

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The bread-making quality of wheat is strongly influenced by multiple low molecular weight glutenin subunit (LMW-GS) proteins expressed in the seeds. However, the organization, recombination and expression of LMW-GS genes and their functional mechanism in bread-making are not well understood. Here we report a systematic molecular analysis of LMW-GS genes located at the orthologous Glu-3 loci (Glu-A3, B3 and D3) of bread wheat using complementary approaches (genome wide characterization of gene members, expression profiling, proteomic analysis). Fourteen unique LMW-GS genes were identified for Xiaoyan 54 (with superior bread-making quality). Molecular mapping and recombination analyses revealed that the three Glu-3 loci of Xiaoyan 54 harbored dissimilar numbers of LMW-GS genes and covered different genetic distances. The number of expressed LMW-GS in the seeds was higher in Xiaoyan 54 than in Jing 411 (with relatively poor bread-making quality)This correlated with the finding of higher numbers of active LMW-GS genes at the A3 and D3 loci in Xiaoyan 54. Association analysis using recombinant inbred lines suggested that positive interactions, conferred by genetic combinations of the Glu-3 locus alleles with more numerous active LMW-GS genes, were generally important for the recombinant progenies to attain high Zeleny sedimentation value (ZSV), an important indicator of bread-making quality. A higher number of active LMW-GS genes tended to lead to a more elevated ZSV, although this tendency was influenced by genetic background. This work provides substantial new insights into the genomic organization and expression of LMW-GS genes, and molecular genetic evidence suggesting that these genes contribute quantitatively to bread-making quality in hexaploid wheat. Our analysis also indicates that selection for high numbers of active LMW-GS genes can be used for improvement of bread-making quality in wheat breeding.

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Section: Resultssupporting

confidence: 90%

“…ZSV was again chosen as the evaluation parameter based on our earlier QTL investigation. This choice was also supported by the published literature showing that ZSV correlated positively with gluten strength and bread volume [62] - [64] , and that the genetic composition of Glu-3 loci affected ZSV [65] - [68] .…”

Section: Resultssupporting

confidence: 70%

New Insights into the Organization, Recombination, Expression and Functional Mechanism of Low Molecular Weight Glutenin Subunit Genes in Bread Wheat

et al. 2010

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“…Although the QTLs detected in our study and the ones detected in another study on Canadian wheat by Huang et al (2006) are different, the phenotypic variation explained by all of the QTLs was comparable. In contrast to those results obtained in earlier studies for QTL effects in grain protein content only or those identified for flour protein content only (Snape et al 1995;Blanco et al 1996Blanco et al , 2002Prasad et al 1999Prasad et al , 2003Zanetti et al 1999Zanetti et al , 2001Harjit-Singh Prasad et al 2001;Groos et al 2003;Turner et al 2004;Kulwal et al 2005), no such four 'stable' QTL have identified for both grain protein content and flour protein content of bread wheat and reported to date.…”

Section: Discussioncontrasting

confidence: 81%

“…Flour protein content is subject to genetic effects, as is grain protein content. However, many of studies carried out to date on QTLs in wheat have focused only on grain protein content or only identified the flour protein content (Snape et al 1995;Blanco et al 1996Blanco et al , 2002Prasad et al 1999Prasad et al , 2003Zanetti et al 1999Zanetti et al , 2001Harjit-Singh Prasad et al 2001;Groos et al 2003;Turner et al 2004;Kulwal et al 2005).…”

Section: Discussionmentioning

confidence: 97%

A comparison of grain protein content QTLs and flour protein content QTLs across environments in cultivated wheat

et al. 2010

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The protein content of cultivated wheat (Triticum aestivum L.) is an important determinant factor of the nutritional value of the grain and the technological properties and rheological properties of flour. In order to examine the genetic basis of protein content, we searched for grain protein content quantitative trait loci (QTLs) and flour protein content QTLs in a newly developed doubled haploid (DH) line and identified the genetic correlation between grain protein content and flour protein content in the same DH population. Both the DH population and its parental lines were evaluated for grain protein content and flour protein content in three field trials. Four additive effect QTLs, two pairs of epistatic QTLs, and two QTLs 9 environment (QE) interaction for grain protein content were identified. The model explained 51.52% of the phenotypic variation (PVE), with epistatic effects being better explained by the higher PVE than additive effects. Four additive effect QTLs, five pairs of epistatic QTLs, and one QE were detected for flour protein content. The model explained 45.8% of the PVE. Of the 15 QTLs identified, three additive QTLs and one pair of epistatic QTLs were determined for both grain protein content and flour protein content; of these, the QTLs for protein content were considered to be more 'stable' than those detected for only grain protein content or for only flour protein content. The data reported here may be useful for manipulating the QTLs for protein content by marker-assisted selection in future wheat breeding programs.

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“…Grain protein content is one of the most important factors affecting pastamaking (Matsuo et al 1982;Autran et al 1996) and bread-making quality, and is also important to human nutrition. Many recent reports (Joppa and Cantrell 1990;Sourdille et al 1999;Zanetti et al 1999;Perretant et al 2000;Blanco et al 1996Blanco et al , 2002Blanco et al , 2006 concluded that genetic factors impacting GPC in both cultivars and wild wheat were distributed over all 21 wheat chromosomes. Chee et al (2001) detected a high grain protein QTL, QGpc.ndsu.6Bb, from Triticum turgidum L. var.…”

Section: Introductionmentioning

confidence: 97%

QTL detection of seven quality traits in wheat using two related recombinant inbred line populations

Cui

Ding

et al. 2011

Euphytica

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Grain protein content (GPC) and gluten quality are the most important factors determining the end-use quality of wheat for pasta-making. Both GPC and gluten quality are considered to be polygenic traits influenced by environmental factors and other agricultural practices. Two related F 8:9 recombinant inbred line (RIL) populations were generated to localise genetic factors controlling seven quality traits: GPC, wet gluten content (WGC), flour whiteness (FW), kernel hardness (KH), water absorption (Abs), dough development time (DDT) and dough stability time (DST). These lines were derived by crossing Weimai 8 and Jimai 20 (WJ) and by crossing Weimai 8 and Yannong 19 (WY). In total, WJ comprised 485 lines, while WY comprised 229 lines. Data on these seven quality traits were collected from each line in five different environments. Up to 85 putative QTLs for the seven traits were detected in WJ and 65 putative QTLs were detected in WY. Of these QTLs, 31 QTLs (36.47%) were detected in at least two trials in WJ, while 24 QTLs (36.92%) were detected in at least two trials in WY. Three QTLs from WJ and 25 from WY accounted for more than 10% of the phenotypic variance. The total 150 QTLs were spread throughout all 21 wheat chromosomes. Of these, at least thirteen pairwise were common to both populations, accounting for 20.00 and 15.29% of the total QTLs in WJ and WY, respectively. A major QTL for GPC, accounting for 53.04% of the phenotypic variation, was detected on chromosome 5A. A major QTL for WGC also shared this interval, explained more than 36% of the phenotypic variation, and was significant in two environments. Though colocated QTLs were common, every trait had its unique control mechanism, even for two closely related traits. Due to the different sizes of the two line populations, we also assessed the effects of population size on the efficiency and precision of QTL detection. In sum, this study will enhance our understanding of the genetic basis of these seven pivotal quality traits and facilitate the breeding of improved wheat varieties.

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QTL for quality parameters for bread-making in a segregating wheat by spelt population

Cited by 7 publications

References 3 publications

New Insights into the Organization, Recombination, Expression and Functional Mechanism of Low Molecular Weight Glutenin Subunit Genes in Bread Wheat

New Insights into the Organization, Recombination, Expression and Functional Mechanism of Low Molecular Weight Glutenin Subunit Genes in Bread Wheat

A comparison of grain protein content QTLs and flour protein content QTLs across environments in cultivated wheat

QTL detection of seven quality traits in wheat using two related recombinant inbred line populations

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