Genetic control of wheat quality: interactions between chromosomal regions determining protein content and composition, dough rheology, and sponge and dough baking properties

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.

Wheat end-use quality: State of art, genetics, genomics-assisted improvement, future challenges, and opportunities

Wheat is the most important source of food, feed, and nutrition for humans and livestock around the world. The expanding population has increasing demands for various wheat products with different quality attributes requiring the development of wheat cultivars that fulfills specific demands of end-users including millers and bakers in the international market. Therefore, wheat breeding programs continually strive to meet these quality standards by screening their improved breeding lines every year. However, the direct measurement of various end-use quality traits such as milling and baking qualities requires a large quantity of grain, traits-specific expensive instruments, time, and an expert workforce which limits the screening process. With the advancement of sequencing technologies, the study of the entire plant genome is possible, and genetic mapping techniques such as quantitative trait locus mapping and genome-wide association studies have enabled researchers to identify loci/genes associated with various end-use quality traits in wheat. Modern breeding techniques such as marker-assisted selection and genomic selection allow the utilization of these genomic resources for the prediction of quality attributes with high accuracy and efficiency which speeds up crop improvement and cultivar development endeavors. In addition, the candidate gene approach through functional as well as comparative genomics has facilitated the translation of the genomic information from several crop species including wild relatives to wheat. This review discusses the various end-use quality traits of wheat, their genetic control mechanisms, the use of genetics and genomics approaches for their improvement, and future challenges and opportunities for wheat breeding.

QTL detection for bread wheat processing quality in a nested association mapping population of semi-wild and domesticated wheat varieties

BACKGROUND

Wheat processing quality is an important factor in evaluating overall wheat quality, and dough characteristics are important when assessing the processing quality of wheat. As a notable germplasm resource, semi-wild wheat has a key role in the study of wheat processing quality.

RESULTS

In this study, four dough rheological characteristics were collected in four environments using a nested association mapping (NAM) population consisting of semi-wild and domesticated wheat varieties to identify quantitative trait loci (QTL) for wheat processing quality. A total of 49 QTL for wheat processing quality were detected, explaining 0.36-10.82% of the phenotypic variation. These QTL were located on all wheat chromosomes except for 2D, 3A, 3D, 6B, 6D and 7D. Compared to previous studies, 29 QTL were newly identified. Four novel QTL, QMlPH-1B.4, QMlPH-3B.4, QWdEm-1B.2 and QWdEm-3B.2, were stably identified in three or more environments, among which QMlPH-3B.4 was a major QTL. Moreover, eight important genetic regions for wheat processing quality were identified on chromosomes 1B, 3B and 4D, which showed pleiotropy for dough characteristics. In addition, out of 49 QTL, 15 favorable alleles came from three semi-wild parents, suggesting that the QTL alleles provided by the semi-wild parent were not utilized in domesticated varieties.

CONCLUSIONS

The results show that semi-wild wheat varieties can enrich the existing wheat gene pool and provide broader variation resources for wheat genetic research.

Genetic Dissection of the Mixing Properties of Wheat Flour (Triticum aestivum L.) Using Unconditional and Conditional QTL Mapping

Wheat (Triticum aestivum L.) flour mixing properties are essential quality parameters in the dough development process. Limited research on superior alleles for mixing properties has restricted their molecular improvement, and other factors related to the complex traits have been ignored. A molecular map of 9576 polymorphic markers in the RIL population (F_8:9) (Shannong01-35/Gaocheng9411) was constructed to evaluate mixing property effects in three environments. The parents were selected with markedly distinct high-molecular-weight glutenin subunits (HMW-GS). This study not only evaluated mixing properties using conventional unconditional QTL mapping but also evaluated the relationships between protein-related traits using conditional QTL mapping. The analyses identified most additive QTLs for major mixing properties on chromosomes 1A, 1B, and 1D. Two major loci (1A.1-15 and 1D-1) associated with mixing properties have confirmed the important contributions of Glu-A1 and Glu-D1 to wheat quality at the QTL level, which were mainly affected by the gluten index. Another important locus, 1B.1-24 (associated with midline peak value and midline peak width, with high phenotypic variations explained), might represent a new variation distinct from Glu-B1. The favored alleles came from Gaocheng9411. Several mixing properties shared the same QTLs (1B.1-6 and 1A.1-15), indicating tight linkage or pleiotropism. Genotype-by-environment (G×E) interactions were also investigated in the present study. The QTL results in our study may improve our understanding of the genetic interrelationships between mixing properties and protein-related traits.

Protein Biofortification in Lentils (Lens culinaris Medik.) Toward Human Health

Lentil (Lens culinaris Medik.) is a nutritionally dense crop with significant quantities of protein, low-digestible carbohydrates, minerals, and vitamins. The amino acid composition of lentil protein can impact human health by maintaining amino acid balance for physiological functions and preventing protein-energy malnutrition and non-communicable diseases (NCDs). Thus, enhancing lentil protein quality through genetic biofortification, i.e., conventional plant breeding and molecular technologies, is vital for the nutritional improvement of lentil crops across the globe. This review highlights variation in protein concentration and quality across Lens species, genetic mechanisms controlling amino acid synthesis in plants, functions of amino acids, and the effect of antinutrients on the absorption of amino acids into the human body. Successful breeding strategies in lentils and other pulses are reviewed to demonstrate robust breeding approaches for protein biofortification. Future lentil breeding approaches will include rapid germplasm selection, phenotypic evaluation, genome-wide association studies, genetic engineering, and genome editing to select sequences that improve protein concentration and quality.

Identification of Genetic Loci and Candidate Genes Related to Grain Zinc and Iron Concentration Using a Zinc-Enriched Wheat 'Zinc-Shakti'

The development of nutritionally enhanced wheat (Triticum aestivum L.) with higher levels of grain iron (Fe) and zinc (Zn) offers a sustainable solution to micronutrient deficiency among resource-poor wheat consumers. One hundred and ninety recombinant inbred lines (RILs) from 'Kachu' × 'Zinc-Shakti' cross were phenotyped for grain Fe and Zn concentrations and phenological and agronomically important traits at Ciudad Obregon, Mexico in the 2017-2018, 2018-2019, and 2019-2020 growing seasons and Diversity Arrays Technology (DArT) molecular marker data were used to determine genomic regions controlling grain micronutrients and agronomic traits. We identified seven new pleiotropic quantitative trait loci (QTL) for grain Zn and Fe on chromosomes 1B, 1D, 2B, 6A, and 7D. The stable pleiotropic QTL identified have expanded the diversity of QTL that could be used in breeding for wheat biofortification. Nine RILs with the best combination of pleiotropic QTL for Zn and Fe have been identified to be used in future crossing programs and to be screened in elite yield trials before releasing as biofortified varieties. In silico analysis revealed several candidate genes underlying QTL, including those belonging to the families of the transporters and kinases known to transport small peptides and minerals (thus assisting mineral uptake) and catalyzing phosphorylation processes, respectively.

From Genetic Maps to QTL Cloning: An Overview for Durum Wheat

Durum wheat is one of the most important cultivated cereal crops, providing nutrients to humans and domestic animals. Durum breeding programs prioritize the improvement of its main agronomic traits; however, the majority of these traits involve complex characteristics with a quantitative inheritance (quantitative trait loci, QTL). This can be solved with the use of genetic maps, new molecular markers, phenotyping data of segregating populations, and increased accessibility to sequences from next-generation sequencing (NGS) technologies. This allows for high-density genetic maps to be developed for localizing candidate loci within a few Kb in a complex genome, such as durum wheat. Here, we review the identified QTL, fine mapping, and cloning of QTL or candidate genes involved in the main traits regarding the quality and biotic and abiotic stresses of durum wheat. The current knowledge on the used molecular markers, sequence data, and how they changed the development of genetic maps and the characterization of QTL is summarized. A deeper understanding of the trait architecture useful in accelerating durum wheat breeding programs is envisioned.

Differences in Processing Quality Traits, Protein Content and Composition between Spelt and Bread Wheat Genotypes Grown under Conventional and Organic Production

The unique rheological properties of bread wheat dough and the breadmaking quality of its flour are the main factors responsible for the global distribution and utilization of wheat. Recently, interest in the production and expansion of spelt wheat has been boosted due to its significance in the production of healthy food, mostly originated from organic production. The aim of this study was to examine and compare quality parameters (gluten content, Zeleny sedimentation volume, farinograph dough properties), protein content and composition (by the Dumas method, Size Exclusion (SE) and Reversed Phase (RP) High Performance Liquid Chromatography (HPLC) analyses) of five bread and five spelt wheat varieties grown under conventional and organic production in Hungary and under conventional production in Serbia. Most of the analyzed traits showed significant differences between varieties, wheat species and growing sites. Total protein content was significantly higher in spelt than in bread wheat and under conventional than under organic production. In comparison to spelt, bread wheat showed better breadmaking quality, characterized by a higher amount of glutenins (in particular high molecular weight glutenin subunits) and unextractable polymeric proteins. The proportion of the gliadins was also found to be different under conventional and organic systems. Spelt Ostro and Oberkulmer-Rotkorn and bread wheat varieties Balkan, Estevan and Pobeda proved suitable for low input and organic systems.

Contribution to Breadmaking Performance of Two Different HMW Glutenin 1Ay Alleles Expressed in Hexaploid Wheat

Two expressed alleles of the 1Ay high-molecular-weight glutenin subunit (HMW-GS), 1Ay21* and 1AyT1, previously introduced in durum and bread wheat, were separately introgressed into the Australian bread wheat (Triticum aestivum L.) cv. Livingston. The developed lines had different allelic compositions compared to that of the parental cultivar (1Ax1), having either 1Ax21+1Ay21* or 1Ax1+1AyT1 at the Glu-A1 locus. Since 1Ax21 and 1Ax1 are known to have the same effects on quality, differences observed between the two sets of the developed lines are attributed to the two introgressed Ay genes. Yield and agronomic performance of the lines were evaluated in the field, and the protein, dough, and baking quality attributes were evaluated by large-scale quality testing. Results demonstrated that the subunit 1Ay21* increased unextractable polymeric protein by up to 14.3% and improved bread loaf volume by up to 9.2%. On the other hand, subunit 1AyT1 increased total grain protein by up to 9% along with dough elasticity. Furthermore, milling extraction was higher, and flour ash was lower in the 1Ay21* lines compared to the lines integrating 1AyT1. Both sets of the 1Ay introgression lines reduced dough-mixing time compared to the recurrent parent Livingston. The results also showed that 1Ay21* had a higher potential to improve the baking quality than 1AyT1 under the Livingston genetic background. Both alleles showed the potential to be utilized in breeding programs to improve the breadmaking quality.

QTL analysis of farinograph and mixograph related traits in spring wheat under heat stress conditions

Farinograph and mixograph-related parameters are key elements in wheat end-products quality. Understanding the genetic control of these traits and the influence of environmental factors such as heat stress, and their interaction are critical for developing cultivars with improved for those traits. To identify QTL for six farinograph and three mixograph traits, two double haploid (DH) populations (Yecora Rojo × Ksu106 and Klasic × Ksu105) were used in experiments conducted at Riyadh and Al Qassim locations under heat stress. Single nucleotide polymorphism (SNP) markers were used to determine the number of QTLs controlling these parameters. The genetic analysis of farinograph and mixograph-related traits showed considerable variation with transgressive segregation regardless of heat stress conditions in both locations. A total of 108 additive QTLs were detected for the six farinograph and three mixograph traits in the Yecora Rojo × Ksu106 population in both locations under heat treatments. These QTLs were distributed over all 21 wheat chromosomes except 3A. Similarly, in Klassic × Ksu105 population, there were an additional 68 QTLs identified over the two locations and were allocated on all chromosomes except 1D, 2A, 6A, and 6D. In population (Yecora Rojo × Ksu106), the QTL on chromosome 7A (Excalibur_c62415_288) showed significant effects for farinograph and mixograph traits (FDDT, FDST, FBD, M × h8, and M × t) under normal and heat stress condition at both locations. Interestingly, several QTLs that are related to farinograph and mixograph traits, which showed stable expression under both locations, were detected on chromosome 7A in population (Klassic × Ksu105). Results from this study show the quantitative nature of the genetic control of the studied traits and constitute a step toward identifying major QTLs that can be sued molecular-marker assisted breeding to develop new improved quality wheat cultivars.

QTL mapping for quality traits using a high-density genetic map of wheat

Protein- and starch-related quality traits, which are quantitatively inherited and significantly influenced by the environment, are critical determinants of the end-use quality of wheat. We constructed a high-density genetic map containing 10,739 loci (5,399 unique loci) using a set of 184 recombinant inbred lines (RILs) derived from a cross of 'Tainong 18 × Linmai 6' (TL-RILs). In this study, a quantitative trait loci (QTLs) analysis was used to examine the genetic control of grain protein content, sedimentation value, farinograph parameters, falling number and the performance of the starch pasting properties using TL-RILs grown in a field for three years. A total of 106 QTLs for 13 quality traits were detected, distributed on the 21 chromosomes. Of these, 38 and 68 QTLs for protein- and starch-related traits, respectively, were detected in three environments and their average values (AV). Twenty-six relatively high-frequency QTLs (RHF-QTLs) that were detected in more than two environments. Twelve stable QTL clusters containing at least one RHF-QTL were detected and classified into three types: detected only for protein-related traits (type I), detected only for starch-related traits (type II), and detected for both protein- and starch-related traits (type III). A total of 339 markers flanked with 11 QTL clusters (all except C6), were found to be highly homologous with 282 high confidence (HC) and 57 low confidence (LC) candidate genes based on IWGSC RefSeq v 1.0. These stable QTLs and RHF-QTLs, especially those grouped into clusters, are credible and should be given priority for QTL fine-mapping and identification of candidate genes with which to explain the molecular mechanisms of quality development and inform marker-assisted breeding in the future.

Introgression of an expressed HMW 1Ay glutenin subunit allele into bread wheat cv. Lincoln increases grain protein content and breadmaking quality without yield penalty

An expressed HMW glutenin subunit Glu-Ay showed positive impacts on a range of wheat processing quality and yield traits. The grain protein compositions are significantly optimised for baking, resulting in a better breadmaking quality. The unique breadmaking properties of wheat flour are related to the quality and quantity of high-molecular weight glutenin subunits (HMW-GSs) present in the grain. In the current study, the silent 1Ay HMW-GS allele, present in most bread wheat cultivars, was replaced by the expressed 1Ay21* allele, which was introgressed into Australian bread wheat cultivar Lincoln by a backcrossing and selfing scheme. Stability of gene expression and the effect of the introgressed 1Ay21* subunit on protein composition, agronomic traits, flour functionality, and breadmaking quality were studied using BC4F5 grain grown in glasshouse and field. Field phenotyping and grain quality testing showed that the 1Ay21* gene conferred significant improvements to a range of traits, including an increase in grain protein content by up to 9%, UPP% by up to 24%, bread volume by up to 28%. The glasshouse experiment and one of the field trials showed positive 1Ay21* effects on yield, while one field trial showed one significant effects. This indicates that expression of the 1Ay21* gene has the potential of simultaneously increasing protein content and grain yield under certain environment. The qualitative improvements of the grain also led to a reduction of the energy required during the baking process in addition to the significant positive effects on bread quality.

Genome wide genetic dissection of wheat quality and yield related traits and their relationship with grain shape and size traits in an elite × non-adapted bread wheat cross

The genetic gain in yield and quality are two major targets of wheat breeding programs around the world. In this study, a high density genetic map consisting of 10,172 SNP markers identified a total of 43 genomic regions associated with three quality traits, three yield traits and two agronomic traits in hard red spring wheat (HRSW). When compared with six grain shape and size traits, the quality traits showed mostly independent genetic control (~18% common loci), while the yield traits showed moderate association (~53% common loci). Association of genomic regions for grain area (GA) and thousand-grain weight (TGW), with yield suggests that targeting an increase in GA may help enhancing wheat yield through an increase in TGW. Flour extraction (FE), although has a weak positive phenotypic association with grain shape and size, they do not share any common genetic loci. A major contributor to plant height was the Rht8 locus and the reduced height allele was associated with significant increase in grains per spike (GPS) and FE, and decrease in number of spikes per square meter and test weight. Stable loci were identified for almost all the traits. However, we could not find any QTL in the region of major known genes like GPC-B1, Ha, Rht-1, and Ppd-1. Epistasis also played an important role in the genetics of majority of the traits. In addition to enhancing our knowledge about the association of wheat quality and yield with grain shape and size, this study provides novel loci, genetic information and pre-breeding material (combining positive alleles from both parents) to enhance the cultivated gene pool in wheat germplasm. These resources are valuable in facilitating molecular breeding for wheat quality and yield improvement.

Deciphering the Genetics of Major End-Use Quality Traits in Wheat

Improving the end-use quality traits is one of the primary objectives in wheat breeding programs. In the current study, a population of 127 recombinant inbred lines (RILs) derived from a cross between Glenn (PI-639273) and Traverse (PI-642780) was developed and used to identify quantitative trait loci (QTL) for 16 end-use quality traits in wheat. The phenotyping of these 16 traits was performed in nine environments in North Dakota, USA. The genotyping for the RIL population was conducted using the wheat Illumina iSelect 90K SNP assay. A high-density genetic linkage map consisting of 7,963 SNP markers identified a total of 76 additive QTL (A-QTL) and 73 digenic epistatic QTL (DE-QTL) associated with these traits. Overall, 12 stable major A-QTL and three stable DE-QTL were identified for these traits, suggesting that both A-QTL and DE-QTL played an important role in controlling end-use quality traits in wheat. The most significant A-QTL (AQ.MMLPT.ndsu.1B) was detected on chromosome 1B for mixograph middle line peak time. The AQ.MMLPT.ndsu.1B A-QTL was located very close to the position of the Glu-B1 gene encoding for a subunit of high molecular weight glutenin and explained up to 24.43% of phenotypic variation for mixograph MID line peak time. A total of 23 co-localized QTL loci were detected, suggesting the possibility of the simultaneous improvement of the end-use quality traits through selection procedures in wheat breeding programs. Overall, the information provided in this study could be used in marker-assisted selection to increase selection efficiency and to improve the end-use quality in wheat.

Analysis of genetic control and QTL mapping of essential wheat grain quality traits in a recombinant inbred population

Wheat cultivars are genetically crossed to improve end-use quality for traits as per demands of baking industry and broad consumer preferences. The processing and baking qualities of bread wheat are influenced by a variety of genetic make-ups, environmental factors and their interactions. Two wheat cultivars, WL711 and C306, derived recombinant inbred lines (RILs) with a population of 206, were used for phenotyping of quality-related traits. The genetic analysis of quality traits showed considerable variation for measurable quality traits, with normal distribution and transgressive segregation across the years. From the 206 RILs, few RILs were found to be superior to those of the parental cultivars for key quality traits, indicating their potential use for the improvement of end-use quality and suggesting the probability of finding new alleles and allelic combinations from the RIL population. Mapping analysis identified 38 putative QTLs for 13 quality-related traits, with QTLs explaining 7.9-16.8% phenotypic variation spanning over 14 chromosomes, i.e., 1A, 1B, 1D, 2A, 2D, 3B, 3D, 4A, 4B, 4D, 5D, 6A, 7A and 7B. In-silico analysis based on homology to the annotated wheat genes present in database, identified six putative candidate genes within QTL for total grain protein content, qGPC.1B.1 region. Major QTL regions for other quality traits such as TKW have been identified on 1B, 2A, and 7A chromosomes in the studied RIL population. This study revealed the importance of the combination of stable QTLs with region-specific QTLs for better phenotyping, and the QTLs presented in our study will be useful for the improvement of wheat grain and bread-making quality.

Independent and combined effects of elevated CO2 and post-anthesis heat stress on protein quantity and quality in spring wheat grains

Spring wheat plants were grown under two CO₂ concentrations (380 and 550 μmol mol^-1) and two temperature treatments (ambient and post-anthesis heat stress) to investigate the effects of elevated CO₂ and heat stress on grain protein quality. Contents of protein components, glutenin macropolymers (GMP) and amino acids in grains decreased due to elevated CO₂, while increased by high temperature. The combination of elevated CO₂ and heat stress increased the contents of total protein and albumin, but decreased the contents of gliadin and glutenin, while the content and particle size distribution of GMP as well as the contents of amino acids were not significantly affected. Furthermore, we found that the content and particle size distribution of GMP were not only determined by the contents of proteins and high-molecular-weight glutenin subunits, but also related to the contents of amino acids containing disulfide bonds, which favor the formation of large insoluble polymers.

Improving the baking quality of bread wheat by genomic selection in early generations

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

The influence of Glu-1 and Glu-3 loci on dough rheology and bread-making properties in wheat (Triticum aestivum L.) doubled haploid lines

BACKGROUND

The major determinants of wheat quality are Glu-1 and Glu-3 glutenin loci and environmental factors. Additive effects of alleles at the Glu-1 and Glu-3 loci, as well as their interactions, were evaluated for dough rheology and baking properties in four groups of wheat doubled haploid lines differing in high- and low-molecular-weight glutenin composition.

RESULTS

Flour quality, Reomixer (Reologica Instruments, Lund, Sweden), dough extension, Farinograph (Brabender GmbH, Duisburg, Germany) and baking parameters were determined. Groups of lines with the alleles Glu-A3b and Glu-B3d were characterized by higher values of dough and baking parameters compared to those with the Glu-A3e and Glu-B3a alleles. Effects of interactions between allelic variants at the Glu-1 and Glu-3 loci on Reomixer parameters, dough extension tests and baking parameters were significant, although additive effects of individual alleles were not always significant.

CONCLUSION

The allelic variants at Glu-B3 had a much greater effect on dough rheological parameters than the variants at Glu-A3 or Glu-D3 loci. The effect of allelic variations at the Glu-D3 loci on rheological parameters and bread-making quality was non-significant, whereas their interactions with a majority of alleles at the other Glu-1 × Glu-3 loci were significant. © 2017 Society of Chemical Industry.

Exotic QTL improve grain quality in the tri-parental wheat population SW84

Developing the tri-parental exotic wheat population SW84

Genetic diversity of cultivated wheat was markedly reduced, first, during domestication and, second, since the onset of modern elite breeding. There is an increasing demand for utilizing genetic resources to increase genetic diversity and, simultaneously, to improve agronomic performance of cultivated wheat. To locate favorable effects of exotic wheat alleles, we developed the tri-parental wheat population SW84. The population was derived from crossing the hexaploid spring wheat cultivars Triso and Devon with one synthetic exotic donor accession, Syn084L, followed by two rounds of backcrossing and three rounds of selfing. SW84 consists of 359 BC₂F₄ lines, split into two families, D84 (Devon*Syn084L) and T84 (Triso*Syn084L).

Studying the genetic control of grain quality in SW84

As a case study, grain quality of SW84 was studied in replicated field trials. Transgressive segregation was observed for all studied grain quality traits by evaluating SW84 for two years at two locations under low and high nitrogen supply. Subsequently, a genome-wide association study (GWAS) was carried out based on genomic data derived from a 90k Infinium iSELECT single nucleotide polymorphism (SNP) array. In total, GWAS yielded 37 marker-trait associations, summarized to 16 quantitative trait loci (QTL). These SNPs indicate genetic regulators of grain protein content, grain hardness, sedimentation value and sedimentation ratio. The majority of exotic QTL alleles (75%) exerted favorable effects, increasing grain protein content and sedimentation value in ten and two cases, respectively. For instance, two exotic QTL alleles were associated with a substantial increase of grain protein content and sedimentation value by 1.09% and 7.31 ml, respectively. This finding confirms the potential of exotic germplasm to improve grain quality in cultivated wheat. So far, the molecular nature of most of the detected QTL is unknown. However, two QTL correspond to known genes controlling grain quality: The major QTL on chromosome 6B, increasing grain protein content by 0.70%, on average, co-localizes with the NAM-B1 gene, known to control grain protein content as well as iron and zinc content. Likewise, the major QTL on chromosome 5D, reducing grain hardness by 8.98%, on average, co-localizes with the gene for puroindoline b (Pinb-D1) at the Ha locus. In total, 13 QTL were detected across families, whereas one and three QTL were exclusively detected in families D84 and T84, respectively. Likewise, ten QTL were detected across nitrogen treatments, whereas one and five QTL were exclusively detected under low and high N treatments, respectively. Our data indicate that most effects in SW84 act across families and N levels. Merging of data from two families or two N treatments may, thus, be considered in association studies to increase sample size and, as a result, QTL detection power.

Utilizing favorable exotic QTL alleles in wheat breeding

Our study serves as a model how favorable exotic QTL alleles can be located in exotic germplasm of wheat. In future, the localized favorable exotic QTL alleles will be utilized in wheat breeding programs to simultaneously improve grain quality and selectively expand genetic diversity of the elite wheat gene pool.

Quality and Safety Aspects of Cereals (Wheat) and Their Products

Cereals and, most specifically, wheat are described in this chapter highlighting on their safety and quality aspects. Moreover, wheat quality aspects are adequately addressed since they are used to characterize dough properties and baking quality. Determination of dough properties is also mentioned and pasta quality is also described in this chapter. Chemometrics-multivariate analysis is one of the analyses carried out. Regarding production weighing/mixing of flours, kneading, extruded wheat flours, and sodium chloride are important processing steps/raw materials used in the manufacturing of pastry products. Staling of cereal-based products is also taken into account. Finally, safety aspects of cereal-based products are well documented with special emphasis on mycotoxins, acrylamide, and near infrared methodology.

Interactions between Glu-1 and Glu-3 loci and associations of selected molecular markers with quality traits in winter wheat (Triticum aestivum L.) DH lines

The quality of wheat depends on a large complex of genes and environmental factors. The objective of this study was to identify quantitative trait loci controlling technological quality traits and their stability across environments, and to assess the impact of interaction between alleles at loci Glu-1 and Glu-3 on grain quality. DH lines were evaluated in field experiments over a period of 4 years, and genotyped using simple sequence repeat markers. Lines were analysed for grain yield (GY), thousand grain weight (TGW), protein content (PC), starch content (SC), wet gluten content (WG), Zeleny sedimentation value (ZS), alveograph parameter W (APW), hectolitre weight (HW), and grain hardness (GH). A number of QTLs for these traits were identified in all chromosome groups. The Glu-D1 locus influenced TGW, PC, SC, WG, ZS, APW, GH, while locus Glu-B1 affected only PC, ZS, and WG. Most important marker-trait associations were found on chromosomes 1D and 5D. Significant effects of interaction between Glu-1 and Glu-3 loci on technological properties were recorded, and in all types of this interaction positive effects of Glu-D1 locus on grain quality were observed, whereas effects of Glu-B1 locus depended on alleles at Glu-3 loci. Effects of Glu-A3 and Glu-D3 loci per se were not significant, while their interaction with alleles present at other loci encoding HMW and LMW were important. These results indicate that selection of wheat genotypes with predicted good bread-making properties should be based on the allelic composition both in Glu-1 and Glu-3 loci, and confirm the predominant effect of Glu-D1d allele on technological properties of wheat grains.

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

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. 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 low- and high-N treatments. We identified 109 putative additive QTLs for 11 kernel size and quality characteristics and 49 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.

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.

New QTL alleles for quality-related traits in spring wheat revealed by RIL population derived from supernumerary × non-supernumerary spikelet genotypes

A population developed from an exotic line with supernumerary spikelets was genetically dissected for eight quality traits, discovering new genes/alleles with potential use in wheat breeding programs. Identifying new QTLs and alleles in exotic germplasm is paramount for further improvement of quality traits in wheat. In the present study, an RIL population developed from a cross of an elite wheat line (WCB414) and an exotic genotype with supernumerary spikelets (SS) was used to identify QTLs and new alleles for eight quality traits. Composite interval mapping for 1,000 kernels weight (TKW), kernel volume weight (KVW), grain protein content (GPC), percent of flour extraction (FE) and four mixograph-related traits identified a total of 69 QTLs including 19 stable QTLs. These QTLs were located on 18 different chromosomes (except 4D, 5D, and 6D). Thirteen of these QTLs explained more than 15% of phenotypic variation (PV) and were considered as major QTLs. In this study, we identified 11 QTLs for TKW (R (2) = 7.2-17.1 %), 10 for KVW (R (2) = 6.7-22.5%), 11 for GPC (R (2) = 4.7-16.9%), 6 for FE (R (2) = 4.8-19%) and 31 for mixograph-related traits (R (2) = 3.2-41.2%). In this population, several previously identified QTLs for SS, nine spike-related and ten agronomic traits were co-located with the quality QTLs, suggesting pleiotropic effects or close linkage among loci. The traits GPC and mixogram-related traits were positively correlated with SS. Indeed, several loci for quality traits were co-located with QTL for SS. The exotic parent contributed positive alleles that increased PV of the traits at 56% of loci demonstrating the suitability of germplasm with SS to improve quality traits in wheat.

Conditional QTL mapping of protein content in wheat with respect to grain yield and its components

Grain protein content in wheat (Triticum aestivum L.) is generally considered a highly heritable character that is negatively correlated with grain yield and yield-related traits. Quantitative trait loci (QTL) for protein content was mapped using data on protein content and protein content conditioned on the putatively interrelated traits to evaluate possible genetic interrelationships between protein content and yield, as well as yield-related traits. Phenotypic data were evaluated in a recombinant inbred line population with 302 lines derived from a cross between the Chinese cultivar Weimai 8 and Luohan 2. Inclusive composite interval mapping using IciMapping 3.0 was employed for mapping unconditional and conditional QTL with additives. A strong genetic relationship was found between protein content and grain yield, and yield-related traits. Unconditional QTL mapping analysis detected seven additive QTL for protein content, with additive effects ranging in absolute size from 0.1898% to 0.3407% protein content, jointly accounting for 43.45% of the trait variance. Conditional QTL mapping analysis indicated two QTL independent from yield, which can be used in marker-assisted selection for increasing yield without affecting grain protein content. Three additional QTL with minor effects were identified in the conditional mapping. Of the three QTLs, two were identified when protein content was conditioned on yield, which had pleiotropic effects on those two traits. Conditional QTL mapping can be used to dissect the genetic interrelationship between two traits at the individual QTL level for closely correlated traits. Further, conditional QTL mapping can reveal additional QTL with minor effects that are undetectable in unconditional mapping.

Multivariate whole genome average interval mapping: QTL analysis for multiple traits and/or environments

A major aim in some plant-based studies is the determination of quantitative trait loci (QTL) for multiple traits or across multiple environments. Understanding these QTL by trait or QTL by environment interactions can be of great value to the plant breeder. A whole genome approach for the analysis of QTL is presented for such multivariate applications. The approach is an extension of whole genome average interval mapping in which all intervals on a linkage map are included in the analysis simultaneously. A random effects working model is proposed for the multivariate (trait or environment) QTL effects for each interval, with a variance-covariance matrix linking the variates in a particular interval. The significance of the variance-covariance matrix for the QTL effects is tested and if significant, an outlier detection technique is used to select a putative QTL. This QTL by variate interaction is transferred to the fixed effects. The process is repeated until the variance-covariance matrix for QTL random effects is not significant; at this point all putative QTL have been selected. Unlinked markers can also be included in the analysis. A simulation study was conducted to examine the performance of the approach and demonstrated the multivariate approach results in increased power for detecting QTL in comparison to univariate methods. The approach is illustrated for data arising from experiments involving two doubled haploid populations. The first involves analysis of two wheat traits, α-amylase activity and height, while the second is concerned with a multi-environment trial for extensibility of flour dough. The method provides an approach for multi-trait and multi-environment QTL analysis in the presence of non-genetic sources of variation.

Chromosomes 3B and 4D are associated with several milling and baking quality traits in a soft white spring wheat (Triticum aestivum L.) population

Wheat is marketed based on end-use quality characteristics and better knowledge of the underlying genetics of specific quality parameters is essential to enhance the breeding process. A set of 188 recombinant inbred lines from a 'Louise' by 'Penawawa' mapping population was grown in two crop years at two locations in the Pacific Northwest region of the United States and data were collected on 17 end-use quality traits using established quality analysis protocols. Using an established genetic linkage map, composite interval mapping was used to identify QTL associated with 16 of the 17 quality traits. QTL were found on 13 of the 21 wheat chromosomes. A large number of QTL were located on chromosomes 3B and 4D and coincided with traits for milling quality and starch functionality. Chromosome 3B contained 10 QTL, which were localized to a 26.2 cM region. Chromosome 4D contained 7 QTL, all of which were located on an 18.8 cM region of this chromosome. The majority of the alleles for superior end-use quality were associated with the cultivar Louise. The identified QTL detected remained highly significant independent of grain yield and protein quantity. The identification of these QTL for end-use quality gives key insight into the relationship and complexity of end-use quality traits. It also improves our understanding of these relationships, thereby allowing plant breeders to make valuable gains from selection for these important traits.

Quantitative trait loci influencing endosperm texture, dough-mixing strength, and bread-making properties of the hard red spring wheat breeding lines

Wheat end product quality is determined by a complex group of traits including dough viscoelastic characteristics and bread-making properties. Quantitative trait loci (QTL) mapping and analysis were conducted for endosperm texture, dough-mixing strength, and bread-making properties in a population of 139 (MN99394 × MN98550) recombinant inbred lines that were evaluated at three environments in 2006. Based on the genetic map of 534 loci, six QTL were identified for endosperm texture, with the main QTL on chromosomes 1A (R2 = 6.6%–17.3%), 5A (R2 = 6.1%–17.1%), and 5D (R2 = 15.8%–22%). Thirty-four QTL were identified for eight 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 QTL clusters on chromosome 6D. A QTL cluster on chromosome 6D is one of the novel chromosome regions influencing dough-mixing strength and bread-making properties. The QTL for endosperm texture on chromosomes 1A, 5A, and 5B also influenced flour ash content (12.4%–23.3%), flour protein content (10.5%–12.5%), and flour colour (7.7%–13.5%), respectively.

Mapping of main and epistatic effect QTLs associated to grain protein and gluten strength using a RIL population of durum wheat

Quality, specifically protein content and gluten strength are among the main objectives of a durum wheat breeding program. The aim of this work was to validate quantitative trait loci (QTLs) associated with grain protein content (GPC) and gluten strength measured by SDS sedimentation volume (SV) and to find additional QTLs expressed in Argentinean environments. Also, epistatic QTL and QTL x environmental interactions were analyzed. A mapping population of 93 RILs derived from the cross UC1113 x Kofa showing extreme values in gluten quality was used. Phenotypic data were collected along six environments (three locations, two years). Main effect QTLs associated with GPC were found in equivalent positions in two environments on chromosomes 3BS (R(2)=21.0-21.6%) and 7BL (R(2)=12.1-13%), and in one environment on chromosomes 1BS, 2AL, 2BS, 3BL, 4AL, 5AS, 5BL and 7AS. The most important and stable QTL affecting SV was located on chromosome 1BL (Glu-B1) consistently detected over the six environments (R(2)=20.9- 54.2%). Additional QTLs were found in three environments on chromosomes 6AL (R(2)=6.4-12.5%), and in two environments on chromosomes 6BL (R(2)=11.5-12.1%), 7AS (R(2)=8.2-10.2%) and 4BS (R(2)=11-16.4%). In addition, pleiotropic effects were found affecting grain yield, test weight, thousand-kernel-weight and days to heading in some of these QTLs. Epistatic QTLs and QTL x environment interactions were found for both quality traits, mostly for GPC. The flanking markers of the QTLs detected in this work could be efficient tools to select superior genotypes for the mentioned traits.

QTL mapping for quantities of protein fractions in bread wheat (Triticum aestivum L.)

One of the key targets of breeding programs in bread wheat is to improve the end-use quality. The relationships between quantities of protein fractions and dough rheological characters have been well established, but there is little information on the genetic control of quantities of protein fractions. Two hundred and forty F(6) recombinant inbred lines derived from a cross between two Chinese wheat cultivars, PH82-2 and Neixiang 188, were sown at Jiaozuo in Henan province in the 2005-2006 and 2006-2007 cropping seasons, and inclusive composite interval mapping was used to dissect main effect quantitative trait loci (M-QTLs) and digenic epistatic QTLs (E-QTLs) for quantities of protein fractions. A total of 55 M-QTLs and 77 pairs of E-QTLs affecting the quantities of protein fractions including GLU-A1 (QGA1), GLU-B1 (QGB1), GLU-D1 (QGD1), HMW-GS (QHMW), GLU-A3 (QGA3), GLU-B3 (QGB3), LMW-GS (QLMW), glutenin (QGLU) and the ratio of the quantity of glutenin to those of gliadin were identified, with M-QTLs contributing 39.3-95.6% of the phenotypic variance explained (PVE), and E-QTLs accounting for 1.4-33.5% of the PVE. Among the M-QTLs, 33 were consistent in two seasons and in the mean value of two seasons with similar effects in both magnitude and direction, including major genes on HMW and LMW glutenin loci linked to Sec1 and Glu-B1c, Glu-D1d, Glu-A3a, and grain hardness locus Ha, indicating that these genes were the most important determinants of gluten strength, and they might have significant effects on dough properties not only through effects on allelic composition, but also by influencing quantities of protein fractions. The effects of E-QTLs were more influenced by environments, compared with those of M-QTLs, with only two pairs of E-QTLs consistent in two seasons and in the mean value of two seasons. The M-QTLs were detected in 12 marker intervals, all of which involved E-QTLs on quantities of protein fractions, whereas only 40 of 77 pairs of E-QTLs involved intervals in which M-QTLs were detected. The results indicated that besides main effects, epistatic effects were also important factors in determining quantities of protein fractions in wheat.

Association mapping for quality traits in soft winter wheat

Improvement of end-use quality in bread wheat (Triticum aestivum L.) depends on a thorough understanding of the genetic basis of important quality traits. The main goal of our study was to investigate the genetic basis of 1,000-kernel weight, protein content, sedimentation volume, test weight, and starch concentration using an association mapping approach. We fingerprinted 207 diverse European elite soft winter wheat lines with 115 SSR markers and evaluated the genotypes in multi-environment trials. The principal coordinate analysis revealed absence of a clear population but presence of a family structure. Therefore, we used linear mixed models and marker-based kinship matrices to correct for family structure. In genome-wide scans, we detected main effect QTL for all five traits. In contrast, epistatic QTL were only observed for sedimentation volume and test weight explaining a small proportion of the genotypic variation. Consequently, our findings suggested that integrating epistasis in marker-assisted breeding will not lead to substantially increased selection gain for quality traits in soft winter wheat.

New insights into the organization, recombination, expression and functional mechanism of low molecular weight glutenin subunit genes in bread wheat

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.

Sponge and dough bread making: genetic and phenotypic relationships with wheat quality traits

The genetic and phenotypic relationships among wheat quality predictors and sponge and dough bread making were evaluated in a population derived from a cross between an Australian cultivar 'Chara' and a Canadian cultivar 'Glenlea'. The genetic correlation across sites for sponge and dough loaf volume was high; however, phenotypic correlations across sites for loaf volume were relatively low compared with rheological tests. The large difference between sites was most likely due to temperature differences during grain development reflected in a decrease in the percentage of unextractable polymeric protein and mixing time. Predictive tests (mixograph, extensograph, protein content and composition, micro-zeleny and flour viscosity) showed inconsistent and generally poor correlations with end-product performance (baking volume and slice area) at both sites, with no single parameter being effective as a predictor of end-product performance. The difference in the relationships between genetic and phenotypic correlations highlights the requirement to develop alternative methods of selection for breeders and bakers in order to maximise both genetic gain and predictive assessment of grain quality.

Alternative splicing, activation of cryptic exons and amino acid substitutions in carotenoid biosynthetic genes are associated with lutein accumulation in wheat endosperm

Endosperm carotenoid content in wheat is a primary determinant of flour colour and this affects both the nutritional value of the grain and its utility for different applications. Utilising wheat rice synteny two genes, epsilon-cyclase (epsilon-LCY) and phytoene synthase (Psy-A1), were identified as candidate genes for two of the QTL affecting lutein content in wheat endosperm. Analysis of the sequence changes in epsilon-LCY and Psy-A1 revealed possible causal mechanisms for both QTL. A point mutation in epsilon-LCY results in the substitution of a conserved amino acid in the high lutein allele. This substitution has been observed in high lutein-accumulating species from the Gentiales order. In Psy-A1, a sequence duplication at the end of exon 2 creates a new splice site and causes alternative splicing of the transcript and activation of a cryptic exon, resulting in four different transcripts: a wild-type transcript, two transcripts with early terminations and a transcript that would produce an in-frame, albeit longer protein. Only the wild-type splice variant produced an enzymatically active protein and its mRNA abundance was reduced by titration with the other splice variants. This reduction in wild-type mRNA is argued to result in a reduction in PSY protein and thus carotenoid content in wheat.