QTL analysis of quality traits in the spring wheat cross RL4452 × ‘AC Domain’

McCartney, Curt A.; Somers, Daryl J.; Lukow, O. M.; Ames, Nancy; Noll, J. S.; Cloutier, Sylvie; Humphreys, D. G.; McCallum, Brent D.

doi:10.1111/j.1439-0523.2006.01256.x

Cited by 110 publications

(112 citation statements)

References 24 publications

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“…Numerous studies have identified associations between HMW and LMW glutenin subunits and wheat quality (Payne 1987;Perretant et al 2000;Sourdille et al 2003;McCartney et al 2006;Nelson et al 2006;Zhang et al 2008;Li et al 2009;Mann et al 2009;Suprayogi et al 2009;Reif et al 2011;Li et al 2012;Echeverry-Solarte et al 2015). In this study, KN9204 and J411 differed at two HMW glutenin loci (Glu-A1 and Glu-B1) and two LMW glutenin loci (Glu-A3 and Glu-B3).…”

Section: Novel Stable Qtls and Qtl Co-segregation With Known Genesmentioning

confidence: 86%

“…QKh-2D.1 and QTw-2D might have been identified due to the presence of other linked genes. The Rht-B1 gene is associated with physiological processes that affect not only plant height but also yield, grain quality, seedling vigor and adaptability to adverse environments (Fischer and Stockman 1986;Gooding et al 1999Gooding et al , 2012McCartney et al 2006;Zheng et al 2010;Bai et al 2013;Zhang et al 2013;Asif et al 2015). This study indicated that Rht-B1b had negative effects on TKW, KW, KDR, TW, DT, and ZEL.…”

Section: Novel Stable Qtls and Qtl Co-segregation With Known Genesmentioning

confidence: 88%

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QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress

et al. 2015

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QTLs for tolerance to N stress, 27 and 14 of which were stable across the tested environments, respectively. These QTLs were distributed across all wheat chromosomes except for chromosomes 3A, 4D, 6D, and 7B. Eleven QTL clusters that simultaneously affected kernel size-and quality-related traits were identified. At nine locations, 25 of the 49 QTLs for N deficiency tolerance coincided with the QTLs for kernel characteristics, indicating their genetic independence. The feasibility of indirect selection of a superior genotype for kernel size and quality under high-N conditions in breeding programs designed for a lower input management system are discussed. In addition, we specified the functions of Glu-A1, Glu-B1, Glu-A3, Glu-B3, TaCwi-A1, TaSus2, TaGS2-D1, PPO-D1, Rht-B1, and Ha with regard to kernel characteristics and the sensitivities of these characteristics to N stress. This study provides useful information for the genetic improvement of wheat kernel size, quality, and resistance to N stress. Abbreviations GPCGrain protein content WGC Wet gluten content AbstractKey message QTLs for kernel characteristics and tolerance to N stress were identified, and the functions of ten known genes with regard to these traits were specified. Abstract Kernel size and quality characteristics in wheat (Triticum aestivum L.) ultimately determine the end use of the grain and affect its commodity price, both of which are influenced by the application of nitrogen (N) fertilizer. This study characterized quantitative trait loci (QTLs) for kernel size and quality and examined the responses of these traits to low-N stress using a recombinant inbred line population derived from Kenong 9204 × Jing 411. Phenotypic analyses were conducted in five trials that each included lowand high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49Communicated by I. Mackay.F. Cui, X. Fan, and M. Chen contributed equally to this work. Electronic supplementary materialThe online version of this article

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Section: Novel Stable Qtls and Qtl Co-segregation With Known Genesmentioning

confidence: 86%

Section: Novel Stable Qtls and Qtl Co-segregation With Known Genesmentioning

confidence: 88%

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress

et al. 2015

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“…This flanking marker was localized near the distal end of chromosome 7A, but Xwmc83 detected herein was localized at 78.5 cM. A QTL for the color of noodle dough sheets for white salted noodles was located on chromosome 5D in this study, while QTLs for the L and b values of noodle dough sheets for yellow alkaline noodles were previously detected on chromosomes 5B, 5D and 7AL in DH populations of Canadian wheat lines (McCartney et al, 2006). Sadeque and Turner (2010b) found a major QTL for the L value of alkaline noodles on chromosome 2A, with additional QTLs on chromosomes 1A, 1B and 7A.…”

Section: Discussionmentioning

confidence: 79%

Mapping of QTL for Color of Noodle Dough Sheet in a Doubled Haploid Population

Kang¹,

Chen²,

Kim³

et al. 2015

JAS

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This study was conducted for identification of the quantitative trait loci (QTL) associated with the color of flour and noodle dough sheets for the production of white salted noodles by analysis of a doubled haploid population from a cross between Korean wheat cultivars carrying different color values for the flour and noodle dough sheets. The DH population was evaluated in replicated field trials in 2011 and 2012 in upland conditions in Iksan, Korea. The color differences were measured as CIE-LAB L, a and b values. Xgwm190 located on chromosome 5D explained 13.3%-22.8% of the phenotypic variation in the color of flour over the average of two years. Xgwm190 also explained 11.8% and 24.1% of the phenotypic variation for the L and b values of the noodle dough sheets for the average of two years, respectively. Xbarc81 and Xgwm133 accounted for 7.9% and 9.8% of the phenotypic variation in the b value of flour produced in 2012 and the noodle dough sheets from flour produced in 2011, respectively. The putative marker for flour and noodle dough sheet color, Xgwm190, was applied to validate the relationship between genotypes of 24 Korean wheat cultivars. Fourteen of the Korean wheat cultivars contained genotype a, which represented homozygous to Keumkang at Xgwm190, showed lower L values of the flour and noodle dough sheets (91.6 and 83.5, respectively) than genotype b (93.6 and 85.1, respectively), which represented homozygous to Olgeuru at Xgwm190. Xgwm190 could be used for the selection of wheat lines with bright color in Korean wheat breeding programs.

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“…Positive additive allele effects indicate that the QTL for higher value were contributed by MN99394, and negative indicates that the QTL alleles were contributed by MN98550 c The percent phenotypic variation (R 2 × 100) explained by joint effects of all QTL in the multiple regression model Table 2 to be continued McCartney et al 2006;Elangovan et al 2008;Mann et al 2009). The low-molecular weight Glu-A3 locus on 1A influenced SDS-unextractable polymeric proteins (UPP and UVHP), bake water absorption and bake mixing time.…”

Section: Resultsmentioning

confidence: 99%

“…To address this challenge, several research groups have used wheat germplasm covering different market classes to identify quantitative trait loci (QTL) and genes influencing specific end-use quality traits (Campbell et al 2001;McCartney et al 2006;Elangovan et al 2008;Mann et al 2009). In this study, we present QTL influencing major endosperm protein fractions, dough-mixing strength, and bread-making properties in hard red spring wheat breeding lines adapted to the Upper Midwest region of the USA.…”

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confidence: 99%

Quantitative trait loci influencing end-use quality traits of hard red spring wheat breeding lines

Tsilo

Ohm²,

Hareland³

et al. 2011

CZECH J GENET PLANT

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Wheat bread-making quality is influenced by a complex group of traits including dough visco-elastic characteristics. In this study, quantitative trait locus/loci (QTL) mapping and analysis were conducted for endosperm polymeric proteins together with dough mixing strength and bread-making properties in a population of 139 (MN98550 × MN99394) recombinant inbred lines that was evaluated at three environments in 2006. Eleven chromosome regions were associated with endosperm polymeric proteins, explaining 4.2-31.8% of the phenotypic variation. Most of these polymeric proteins QTL coincided with several QTL for dough-mixing strength and bread-making properties. Major QTL clusters were associated with the low-molecular weight glutenin gene Glu-A3, the two high-molecular weight glutenin genes Glu-B1 and Glu-D1, and two regions on chromosome 6D. Alleles at these QTL clusters have previously been proven useful for wheat quality except one of the 6D QTL clusters.

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QTL analysis of quality traits in the spring wheat cross RL4452 × ‘AC Domain’

Cited by 110 publications

References 24 publications

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress

QTL detection for wheat kernel size and quality and the responses of these traits to low nitrogen stress

Mapping of QTL for Color of Noodle Dough Sheet in a Doubled Haploid Population

Quantitative trait loci influencing end-use quality traits of hard red spring wheat breeding lines

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