Genetic analysis of bread‐making quality in wheat and spelt

Zanetti, S.; Winzeler, M.; Feuillet, Catherine; Keller, Beat; Messmer, Monika

doi:10.1046/j.1439-0523.2001.00552.x

Cited by 121 publications

(105 citation statements)

References 27 publications

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“…In addition, genotyping of those markers was laborious and time-consuming. Compared to earlier genetic maps based on SSR and AFLP markers (Groos et al 2003;Hao et al 2003;Sun et al 2010;Xue et al 2008;Zanetti et al 2001;Huang et al 2006) the present map contained mainly SNP markers (86%) and was obtained by using an Infinium iSelect 9 K SNP beadchip array. It comprised 2575 markers spanning 5008.3 cM, with an average distance of 1.9 cM between adjacent markers.…”

Section: Discussionmentioning

confidence: 69%

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Shi

Azam

et al. 2017

Euphytica

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Wheat (Triticum aestivum L.) yield is directly proportional to physio-morphological traits. A high-density genetic map consisting of 2575 markers was used for mapping QTL controlling stay-green and agronomic traits in wheat grown under four diverse water regimes. A total of 108 additive QTL were identified in target traits. Among them, 28 QTL for chlorophyll content (CC) were detected on 11 chromosomes, 43 for normalized difference vegetation index (NDVI) on all chromosomes except 5B, 5D, and 7D, five for spikes per plant (NSP) on different chromosomes, nine for plant height (PH) on four chromosomes, and 23 for thousand-kernel weight (TKW) on 11 chromosomes. Considering all traits, the phenotypic variation explained (PVE) ranged from 3.61 to 41.62%. A major QTL, QNDVI.cgb-5A.7, for NDVI with a maximum PVE of 20.21%, was located on chromosome 5A. A stable and major PH QTL was observed on chromosome 4D with a PVE close to 40%. Most distances between QTL and corresponding flanking markers were less than 1 cM, and approximately one-third of the QTL coincided with markers. Each of 16 QTL clusters on 10 chromosomes controlled more than one trait and therefore could be regarded as pleiotropic regions in response to different water regimes. Forty-one epistatic QTL were identified for all traits having PVE of 6.00 to 25.07%. Validated QTL closely linked to flanking markers will be beneficial for marker-assisted selection in improving drought-tolerance in wheat.

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Section: Discussionmentioning

confidence: 69%

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Shi

Azam

et al. 2017

Euphytica

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“…GPC, particularly glutenin and gliadin content is controlled by a complex genetic system and is strongly affected by the environment. It is an important factor for pasta-making and baking quality and is strongly correlated with WGC, DT, ABS, and ZEL (Zanetti et al 2001;Nelson et al 2006;Suprayogi et al 2009;Li et al 2011). KH, one of the most important determinants of milling yield, has profound effects on the milling, baking and enduse quality of bread wheat ).…”

Section: Introductionmentioning

confidence: 99%

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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“…Additive effect QTL were first identified and epistatic interactions among these additive QTL were then estimated (Zanetti et al 2001). However, this approach usually leaves out many QTL that may have no additive effects, but influence the trait only through epistatic interactions or QTL )environment interactions (QEs) (Ma et al 2005(Ma et al , 2007Rebetzke et al 2007).…”

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confidence: 99%

Detection of quantitative trait loci for paste viscosity characteristics based on the doubled haploid progeny from a cross between two Chinese wheat varieties

Zhao¹,

Zhang²,

Liu³

et al. 2009

Can. J. Plant Sci.

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, J. 2009. Detection of quantitative trait loci for paste viscosity characteristics based on the doubled haploid progeny from a cross between two Chinese wheat varieties. Can. J. Plant Sci. 89: 837Á844. In order to understand the genetic basis of starch pasting viscosity characteristics (the RVA profile, which is produced by the Rapid Visco Analyser) of wheat grain samples, a doubled haploid (DH) population (Huapei 3 )Yumai 57; Yumai 57 is superior to Huapei 3 for RVA profile parameters) and a linkage map consisting of 324 marker loci were used to search QTL. This program was based on mixed linear models and allowed simultaneous mapping of additive effect QTL, epistatic QTL, and QTL )environment interactions (QE). Mapping analysis produced a total of 35 QTL for 6 RVA profile parameters with a single QTL explaining 0.91Á21.34% of phenotypic variations. The 35 QTL were distributed on 15 chromosomes. The QBd-4A had the most significant additive effect, accounting for 21.34% of the phenotypic variance. Two QTL clusters for RVA profile parameters were located on chromosomes 2A and 4A, respectively. The information obtained in this study should be useful for manipulating the QTL for RVA profiles parameters by molecular assisted selection (MAS) in wheat breeding programs.

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Genetic analysis of bread‐making quality in wheat and spelt

Cited by 121 publications

References 27 publications

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

Mapping QTL for stay-green and agronomic traits in wheat under diverse water regimes

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

Detection of quantitative trait loci for paste viscosity characteristics based on the doubled haploid progeny from a cross between two Chinese wheat varieties

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