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Wheat grain yield is generally sink-limited during grain filling. The grain-filling rate (GFR) plays a vital role but is poorly studied due to the difficulty of phenotype surveys. This study explored the grain-filling traits in a recombinant inbred population and wheat collection using two highly saturated genetic maps for linkage analysis and genome-wide association study (GWAS). Seventeen stable additive quantitative trait loci (QTLs) were identified on chromosomes 1B, 4B, and 5A. The linkage interval between IWB19555 and IWB56078 showed pleiotropic effects on GFR1, GFRmax, kernel length (KL), kernel width (KW), kernel thickness (KT), and thousand kernel weight (TKW), with the phenotypic variation explained (PVE) ranging from 13.38% (KW) to 33.69% (TKW). 198 significant marker-trait associations (MTAs) were distributed across most chromosomes except for 3D and 4D. The major associated sites for GFR included IWB44469 (11.27%), IWB8156 (12.56%) and IWB24812 (14.46%). Linkage analysis suggested that IWB35850, identified through GWAS, was located in approximately the same region as QGFRmax2B.3-11, where two high-confidence candidate genes were present. Two important grain weight (GW)-related QTLs colocalized with grain-filling QTLs. The findings contribute to understanding the genetic architecture of the GFR and provide a basic approach to predict candidate genes for grain yield trait QTLs.

Abstract: Dissecting the genetic relationships among gluten-related traits is important for high quality wheat breeding. Quantitative trait loci (QTLs) analysis for gluten strength, as measured by sedimentation volume (SV) and gluten index (GI), was performed using the QTLNetwork 2.0 software. Recombinant inbred lines (RILs) derived from the winter wheat varieties Shannong 01-35×Gaocheng 9411 were used for the study. A total of seven additive QTLs for gluten strength were identified using an unconditional analysis. QGi1D-13 and QSv1D-14 were detected through unconditional and conditional QTLs mapping, which explained 9.15–45.08% of the phenotypic variation. QTLs only identified under conditional QTL mapping were located in three marker intervals: WPT-3743–GLU-D1 (1D), WPT-7001–WMC258 (1B), and WPT-8682–WPT-5562 (1B). Six pairs of epistatic QTLs distributed nine chromosomes were identified. Of these, two main effect QTLs (QGi1D-13 and QSv1D-14) and 12 pairs of epistatic QTLs were involved in interactions with the environment. The results indicated that chromosomes 1B and 1D are important for the improvement of gluten strength in common wheat. The combination of conditional and unconditional QTLs mapping could be useful for a better understanding of the interdependence of different traits at the QTL molecular level.

To dissect the genetic control of the sensory and textural quality traits of Chinese white noodles, a population of recombinant inbred lines (RILs), derived from the cross of waxy wheat Nuomai 1 (NM1) and Gaocheng 8901 (Gc8901), was used. The RILs were tested in three different environments to determine the role of environmental effects on quantitative trait loci (QTL) analysis. A total of 45 QTLs with additive effects for 17 noodle sensory and textural properties under three environments were mapped on 15 chromosomes. These QTLs showed 4.23–42.68% of the phenotypic variance explained (PVE). Nineteen major QTLs were distributed on chromosomes 1B, 1D, 2A, 3B, 3D, 4A, and 6A, explaining more than 10% of the phenotypic variance (PV). Clusters were detected on chromosomes 2B (3 QTLs), 3B (11 QTLs) and 4A (5 QTLs). The cluster detected on chromosome 4A was close to the Wx-B1 marker. Five co-located QTLs with additive effects were identified on chromosomes 2B, 3D, 4A, 6A, and 7B. The two major QTLs, Qadh.sdau-3B.1 and Qspr.sdau-3B.1, in cluster wPt666008–wPt5870 on chromosome 3B were detected in three different environments, which perhaps can be directly applied to improve the textural properties of noodles. These findings could offer evidence for the selection or development of new wheat varieties with noodle quality using molecular marker-assisted selection (MAS).

To evaluate the possible genetic interrelationships between flour components and the sedimentation volume (SD), a doubled haploid (DH) population comprising 168 lines were used to identify the conditional quantitative trait loci (QTLs) for SD in three environments. Ten additive QTLs and 15 pairs of epistatic QTLs were detected for SD through unconditional and conditional QTL mapping. Three major additive QTLs were detected for SD conditioned on the seven quality traits. Two additive QTLs were found to be independent of these traits. Three additive QTLs were suppressed by three of the seven traits because of non-detection in unconditional mapping. Three pairs of epistatic QTLs were completely affected by the seven traits because of detection in unconditional mapping but no-detection in conditional mapping. Twelve pairs of epistatic QTLs were detected in conditional mapping. Our results indicated that conditional mapping could contribute to a better understanding of the interdependence of different and closely correlated traits at the QTL molecular level, especially some minor QTLs were found. The conditional mapping approach provides new insights that will make it possible to avoid the disadvantages of different traits by breeding through molecular design.

Protein and starch are the most important traits in determining processing quality in wheat. In order to understand the genetic basis of the influence of Waxy protein (Wx) and high molecular weight gluten subunit (HMW-GS) on processing quality, 256 recombinant inbred lines (RILs) derived from the cross of waxy wheat Nuomai 1 and Gaocheng 8901 were used as mapping population. DArT (diversity arrays technology), SSR (simple sequence repeat), HMW-GS, and Wx markers were used to construct the molecular genetic linkage map. QTLs for mixing peak time (MPT), mixing peak value (MPV), mixing peak width (MPW), and mixing peak integral (MPI) of Mixograph parameters were evaluated in three different environments. The genetic map comprised 498 markers, including 479 DArT, 14 SSR, 2 HMW-GS, and 3 Wx protein markers, covering 4 229.7 cM with an average distance of 9.77 cM. These markers were identified on 21 chromosomes. Eighteen additive QTLs were detected in three different environments, which were distributed on chromosomes 1A, 1B, 1D, 4A, 6A, and 7D. QMPT-1D.1 and QMPT-1D.2 were close to the Glu-D1 marker accounting for 35.2, 22.22 and 36.57% of the phenotypic variance in three environments, respectively. QMPV-1D and QMPV-4A were detected in all environments, and QMPV-4A was the nearest to Wx-B1. One minor QTL, QMPI-1A, was detected under three environments with the genetic distances of 0.9 cM from the nearest marker Glu-A1, explaining from 5.31 to 6.67% of the phenotypic variance. Three pairs of epistatic QTLs were identified on chromosomes 2D and 4A. Therefore, this genetic map is very important and useful for quality trait related QTL mapping in wheat. In addition, the finding of several major QTLs, based on the genetic analyses, further suggested the importance of Glu-1 loci on dough mixing characteristics.

As one of the most effective enzymatic modification methods of protein, papain hydrolysis is applied widely in food production, accompanying starch pasting frequently in order to improve industrial quality. Effects of the papain hydrolysis on flour pasting properties were investigated in five papain/flour concentrations and five time-treatments. The structure of starch and protein networks in slurry was investigated under microscope before and after pasting. Results showed that papain hydrolysis influenced the pasting properties of wheat flour significantly through affecting structural characteristics, amylase activity and exothermic transition, especially during the early stage of hydrolysis. Peak viscosity, trough, final, integral area, and setback significantly decreased along with the increasing concentration of papain. Both hydrolysis time and concentration of papain had obviously effect on the breakdown. Pasting temperature and pasting time increased significantly with the enhancement of papain concentration. Hydrolysis time exerted minor effect on the pasting temperature and pasting time. The average peak time was slightly prolonged by lower concentration of papain, otherwise slightly shortened by higher concentration.

Kernel hardness (KH) is one of the primary quality parameters for common wheat (Triticum aestivum L.) and has a major impact on milling, flour quality, and end-product properties. In addition to Puroindoline (Pin) mutations and differences in Pin expression, other factors, such as kernel size and protein-related traits, play noticeable roles in determining hardness, but at the quantitative trait locus (QTL) level, the influence of these factors remains unclear. In this study, genetic relationships between KH and kernel size traits and between KH and protein-related traits were demonstrated by unconditional and conditional mapping using a wheat 90K genotyping assay with a segregating population of 173 recombinant inbred lines in four environments. Eight additive QTL for KH were detected using unconditional QTL mapping analysis; these QTL were primarily distributed on chromosomes 4B, 5A, 5B, and 6D, with phenotypic variation that ranged from 0.2 to 17.7%. In addition, one pair of epistatic QTL (QKH3B.4-65/QKH4B.6-2) was identified by unconditional mapping, and this pair accounted for 1.6% of the phenotypic variation. Through conditional mapping, after excluding the influences of kernel size and protein-related traits, 14 QTL were discovered and accounted for 0.6-18.5% of the phenotypic variation. Of them, the stable QTL QKH4B.4-17 made the largest contribution, which was partially contributed by the kernel length (KL), kernel thickness (KT), and dry gluten content (DGC). Furthermore, QKH4B.4-17 was crucially contributed by the kernel width (KW), kernel diameter (KD), kernel protein content (KPC), and wet gluten content (WGC) and was independent of the sedimentation volume (SV) and gluten index (GI). Another major QTL, QKH5B.10-63, was independent of the KWand KT; partly due to the variations in KL, KD, DGC, and WGC; and conclusively contributed by the KPC, SV, and GI. Seven additional QTL were only detected in the conditional analysis and were crucially contributed by kernel size or protein-related traits. These results demonstrated that kernel size and protein-related traits play significant roles in determining KH. The present study increases the understanding of the relationships between KH and kernel size and between KH and protein-related traits at the QTL level. [ABSTRACT FROM AUTHOR]

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 × 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. [ABSTRACT FROM AUTHOR]

Phytic acid is the major storage form for phosphorus in the cereal grains. It exists in the form of mixed salts of Ca–Mg–K (i.e. phytate), and occurs in many locations within the kernel. This form of phosphorus is not available to monogastric animals, including humans, because they lack the enzyme phytase in their digestive tract. In order to permit a better understanding of the functions and heritability of phytic acid, a literature search was conducted to review the development of procedures for the determination of phytic acid. Starting from a basic method of precipitation as insoluble ferric phytate in acid solution, the techniques for the determination of phytic acid have progressed through many kinds of instrumental methods such as colorimetric, synchronous fluorescence, isotachophoresis, high-performance ionic chromatography, and high-performance liquid chromatography. [ABSTRACT FROM AUTHOR]

Flour color is an important trait in the assessment of flour quality for the production of many end products. In this study, quantitative trait loci (QTLs) with additive effects, epistatic effects, and QTL × environment (QE) interactions for flour color in bread wheat ( Triticum aestivum L.) were studied, using a set of 168 doubled haploid (DH) lines derived from a Huapei 3 × Yumai 57 cross. A genetic map was constructed using 283 simple sequence repeats (SSR) and 22 expressed sequence tags (EST)-SSR markers. The DH and parents were evaluated for flour color in three environments. QTL analyses were performed using QTLNetwork 2.0 software based on a mixed linear model approach. A total of 18 additive QTLs and 24 pairs of epistatic QTLs were detected for flour color, which were distributed on 19 of the 21 chromosomes. One major QTL, qa1B, closely linked to barc372 0.1 cM, could account for 25.64% of the phenotypic variation of a* without any influence from the environments. So qa1B could be used in the molecular marker-assisted selection (MAS) in wheat breeding programs. The results showed that both additive and epistatic effects were important genetic basis for flour color, and were also sometimes subject to environmental modifications. The information obtained in this study should be useful for manipulating the QTLs for flour color by MAS in wheat breeding programs. [ABSTRACT FROM AUTHOR]

The cloning and characterization of a novel gene TaCKX1 that encodes cytokinin oxidase/dehydrogenase (CKX) in wheat is described in this work. Using polymerase chain reaction (PCR) technology and degenerate primers derived from conserved regions of published CKX amino acid sequences, a TaCKX1 gene fragment was generated. The 5′ and 3′ flanking sequences of the gene was amplified using inverse PCR. Then, the full-length DNA and complementary DNA sequence of TaCKX1 were cloned. Comparison of the novel genes and wheat CKX gene expressed sequence tag (EST) nucleotide sequences shows that the cloned sequences was highly identical with previously named TaCKX1 EST. Comparison of amino acid sequences from maize, rice, barley, Arabidopsis thaliana, and Dendrobium shows that the TaCKX1 active sites are strongly conserved. The signal peptide, the theoretical p I/MW, the subcellular localization, and the function sites were analyzed. The TaCKX1 gene had been located on chromosome 3A using nulli-tetrasomic lines of “Chinese Spring”. Semi-quantitative reverse transcription polymerase chain reaction analysis showed that the TaCKX1 gene was expressed in root, sheath, and leaf. It could play important roles in wheat growth and development. [ABSTRACT FROM AUTHOR]