Genetic control of grain protein, dough rheology traits and loaf traits in a bread wheat population grown in three environments

TaSED interacts with TaSPA synergistically regulating SDS-sedimentation volume in bread wheat

The SDS-sedimentation volume (SSV) is a critical indicator for assessing wheat gluten quality and is widely used when evaluating wheat processing quality. However, the molecular mechanisms regulating SSV remain poorly understood. In this study, we performed an analysis of quantitative trait loci (QTLs) for SSV using a recombinant inbred line (RIL) population derived from a cross between TAA10 and XX329, and identified four environmentally stable QTLs located on chromosomes 1D, 2D, 4D, and 6D. Among them, the effects of Qssv.cau-1D and Qssv.cau-6D were likely to be explained by genome variations at the Glu-D1 and Gli-D2 loci. We fine mapped Qssv.cau-2D to the candidate causal gene TaSED, encoding a nucleolar protein. Gene-edited TaSED knockout mutants (tased) had a lower SSV, while TaSED overexpression lines showed a higher SSV. We demonstrated that TaSED interacted with the transcription factor TaSPA to enhance its transcriptional activation activity of glutenin and gliadin, whose expression was downregulated in tased and upregulated in TaSED-OE plants, with corresponding differences in glutenin and gliadin content compared with the wild-type. A molecular marker sedTX was further developed based on a nonsynonymous mutation of the parents in TaSED that could be used to identify haplotypes with high SSV effectively. Our findings elucidate a molecular mechanism governing SSV and reveal valuable variants with promising applications for improving wheat quality.

Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.

Striving for Stability in the Dough Mixing Quality of Spring Wheat under the Influence of Prolonged Heat and Drought

The effects of prolonged heat and drought stress and cool growing conditions on dough mixing quality traits of spring wheat (Triticum aestivum L.) were studied in fifty-six genotypes grown in 2017 and 2018 in southern Sweden. The mixing parameters evaluated by mixograph and the gluten protein characteristics studied by size exclusion high-performance liquid chromatography (SE-HPLC) in dough were compared between the two growing seasons which were very different in length, temperature and precipitation. The genotypes varying in gluten strength between the growing seasons (≤5%, ≤12%, and ≤17%) from three groups (stable (S), moderately stable (MS), and of varying stability (VS)) were studied. The results indicate that most of the mixing parameters were more strongly impacted by the interaction between the group, genotype, and year than by their individual contribution. The excessive prolonged heat and drought did not impact the buildup and mixing time expressed as peak time and time 1-2. The gluten polymeric proteins (unextractable, %UPP; total unextractable, TOTU) and large unextractable monomeric proteins (%LUMP) were closely associated with buildup and water absorption in dough. Major significant differences were found in the dough mixing parameters between the years within each group. In Groups S and MS, the majority of genotypes showed the smallest variation in the dough mixing parameters responsible for the gluten strength and dough development between the years. The mixing parameters such as time 1-2, buildup, and peak time (which were not affected by prolonged heat and drought stress) together with the selected gluten protein parameters (%UPP, TOTU, and %LUMP) are essential components to be used in future screening of dough mixing quality in wheat in severe growing environments.

Genetics of the Inverse Relationship between Grain Yield and Grain Protein Content in Common Wheat

Grain protein content (GPC) is one of the most important criteria to determine the quality of common wheat (Triticum aestivum). One of the major obstacles for bread wheat production is the negative correlation between GPC and grain yield (GY). Previous studies demonstrated that the deviation from this inverse relationship is highly heritable. However, little is known about the genetics controlling these deviations in common wheat. To fill this gap, we performed quantitative trait locus (QTL) analysis for GY, GPC, and four derived GY-GPC indices using an eight-way multiparent advanced generation intercross population comprising 394 lines. Interval mapping was conducted using phenotypic data from up to nine environments and genotypic data from a 20k single-nucleotide polymorphism array. The four indices were highly heritable (0.76–0.88) and showed distinct correlations to GY and GPC. Interval mapping revealed that GY, GPC, and GY-GPC indices were controlled by 6, 12, and 12 unique QTL, of which each explained only a small amount of phenotypic variance (R² ≤ 10%). Ten of the 12 index QTL were independent of loci affecting GY and GPC. QTL regions harboured several candidate genes, including Rht-1, WAPO-A1, TaTEF-7A, and NRT2.6-7A. The study confirmed the usefulness of indices to mitigate the inverse GY-GPC relationship in breeding, though the selection method should reflect their polygenic inheritance.

Hybrid wheat: quantitative genetic parameters and heterosis for quality and rheological traits as well as baking volume

Heterosis effects for dough quality and baking volume were close to zero. However, hybrids have a higher grain yield at a given level of bread making quality compared to their parental lines. Bread wheat cultivars have been selected according to numerous quality traits to fulfill the requirements of the bread making industry. These include beside protein content and quality also rheological traits and baking volume. We evaluated 35 male and 73 female lines and 119 of their single-cross hybrids at three different locations for grain yield, protein content, sedimentation value, extensograph traits and baking volume. No significant differences (p < 0.05) were found in the mean comparisons of males, females and hybrids, except for higher grain yield and lower protein content in the hybrids. Mid-parent and better-parent heterosis values were close to zero and slightly negative, respectively, for baking volume and extensograph traits. However, the majority of heterosis values resulted in the finding that hybrids had higher grain yield than lines for a given level of baking volume, sedimentation value or energy value of extensograph. Due to the high correlation with the mid-parent values (r > 0.70), an initial prediction of hybrid performance based on line per se performance for protein content, sedimentation value, most traits of the extensograph and baking volume is possible. The low variance due to specific combining ability effects for most quality traits points toward an additive gene action requires quality selection within both heterotic groups. Consequently, hybrid wheat can combine high grain yield with high bread making quality. However, the future use of wheat hybrids strongly depends on the establishment of a cost-efficient and reliable seed production system.

Combining grain yield, protein content and protein quality by multi-trait genomic selection in bread wheat

KEY MESSAGE

Simultaneous genomic selection for grain yield, protein content and dough rheological traits enables the development of resource-use efficient varieties that combine superior yield potential with comparably high end-use quality. Selecting simultaneously for grain yield and baking quality is a major challenge in wheat breeding, and several concepts like grain protein deviations have been developed for shifting the undesirable negative correlation between both traits. The protein quality is, however, not considered in these concepts, although it is an important aspect and might facilitate the selection of genotypes that use available resources more efficiently with respect to the quantity and quality of the final end products. A population of 480 lines from an applied wheat breeding programme that was phenotyped for grain yield, protein content, protein yield and dough rheological traits was thus used to assess the potential of using integrated genomic selection indices to ease selection decisions with regard to the plethora of quality traits. Additionally, the feasibility of achieving a simultaneous genetic improvement in grain yield, protein content and protein quality was investigated to develop more resource-use efficient varieties. Dough rheological traits related to either gluten strength or viscosity were combined in two separate indices, both of which showed a substantially smaller negative trade-off with grain yield than the protein content. Genomic selection indices based on regression deviations for the two latter traits were subsequently extended by the gluten strength or viscosity indices. They revealed a large merit for identifying resource-use efficient genotypes that combine both superior yield potential with comparably high end-use quality. Hence, genomic selection opens up the opportunity for multi-trait selection in early generations, which will most likely increase the efficiency when developing new and improved varieties.

Genomic Prediction and Genome-Wide Association Studies of Flour Yield and Alveograph Quality Traits Using Advanced Winter Wheat Breeding Material

Use of genetic markers and genomic prediction might improve genetic gain for quality traits in wheat breeding programs. Here, flour yield and Alveograph quality traits were inspected in 635 F6 winter wheat breeding lines from two breeding cycles. Genome-wide association studies revealed single nucleotide polymorphisms (SNPs) on chromosome 5D significantly associated with flour yield, Alveograph P (dough tenacity), and Alveograph W (dough strength). Additionally, SNPs on chromosome 1D were associated with Alveograph P and W, SNPs on chromosome 1B were associated with Alveograph P, and SNPs on chromosome 4A were associated with Alveograph L (dough extensibility). Predictive abilities based on genomic best linear unbiased prediction (GBLUP) models ranged from 0.50 for flour yield to 0.79 for Alveograph W based on a leave-one-out cross-validation strategy. Predictive abilities were negatively affected by smaller training set sizes, lower genetic relationship between lines in training and validation sets, and by genotype-environment (G×E) interactions. Bayesian Power Lasso models and genomic feature models resulted in similar or slightly improved predictions compared to GBLUP models. SNPs with the largest effects can be used for screening large numbers of lines in early generations in breeding programs to select lines that potentially have good quality traits. In later generations, genomic predictions might be used for a more accurate selection of high quality wheat lines.

Optimization of mold wheat bread fortified with soy flour, pea flour and whey protein concentrate

The objective of this work was to study the effect of replacing a selected wheat flour for defatted soy flour, pea flour and whey protein concentrate on both dough rheological characteristics and the performance and nutritional quality of bread. A mixture design was used to analyze the combination of the ingredients. The optimization process suggested that a mixture containing 88.8% of wheat flour, 8.2% of defatted soy flour, 0.0% of pea flour and 3.0% of whey protein concentrate could be a good combination to achieve the best fortified-bread nutritional quality. The fortified bread resulted in high protein concentration, with an increase in dietary fiber content and higher calcium levels compared with those of control (wheat flour 100%). Regarding protein quality, available lysine content was significantly higher, thus contributing with the essential amino acid requirement.

Genome-Wide QTL Mapping for Wheat Processing Quality Parameters in a Gaocheng 8901/Zhoumai 16 Recombinant Inbred Line Population

Dough rheological and starch pasting properties play an important role in determining processing quality in bread wheat (Triticum aestivum L.). In the present study, a recombinant inbred line (RIL) population derived from a Gaocheng 8901/Zhoumai 16 cross grown in three environments was used to identify quantitative trait loci (QTLs) for dough rheological and starch pasting properties evaluated by Mixograph, Rapid Visco-Analyzer (RVA), and Mixolab parameters using the wheat 90 and 660 K single nucleotide polymorphism (SNP) chip assays. A high-density linkage map constructed with 46,961 polymorphic SNP markers from the wheat 90 and 660 K SNP assays spanned a total length of 4121 cM, with an average chromosome length of 196.2 cM and marker density of 0.09 cM/marker; 6596 new SNP markers were anchored to the bread wheat linkage map, with 1046 and 5550 markers from the 90 and 660 K SNP assays, respectively. Composite interval mapping identified 119 additive QTLs on 20 chromosomes except 4D; among them, 15 accounted for more than 10% of the phenotypic variation across two or three environments. Twelve QTLs for Mixograph parameters, 17 for RVA parameters and 55 for Mixolab parameters were new. Eleven QTL clusters were identified. The closely linked SNP markers can be used in marker-assisted wheat breeding in combination with the Kompetitive Allele Specific PCR (KASP) technique for improvement of processing quality in bread wheat.