SNP markers for early identification of high molecular weight glutenin subunits (HMW-GSs) in bread wheat

Identification of new nucleotide sequences of the Glu-B1-1 gene encoding x-type glutenins in bread wheat

Studies of the genetic base and polymorphism of bread wheat cultivars aimed at identifying alleles of genes associated with high baking and other economically valuable traits seem to be relevant, since bread wheat, along with all representatives of the Triticeae tribe, has a huge genetic potential for creating cultivars with high technological and rheological properties of grain flour. The aim of this study was sequencing and analysis of the nucleotide sequences of the Glu-B1-1 gene, and analysis of the predicted amino acid sequences of its protein product in three cultivars of bread wheat. Thus, in the course of genotyping cultivars and lines of bread wheat for the Glu-B1-1 gene, in the cultivars 'Avesta', 'Leningradka krupnozernaya' and line C-75094, previously undescribed changes in the size of amplifiable regions of the Glu-B1-1 gene for high-molecular weight glutenins were found. Comparative analysis of the nucleotide sequences of these genes with known sequences showed the presence of two deletions in 'Avesta' and C-75094 and the presence of seven single-nucleotide substitutions in 'Leningradka krupnozernaya'. Alignment of the predicted Glu-B1 amino acid sequences of the studied accessions and the standard cultivar carrying the Glu-B1-a allele showed that deletions in the amino acid sequences of 'Avesta' and C-75094 accessions are localized in the central domain of the protein and affect the amount of tri-, hexa-, and nonapeptides, and in 'Leningradka krupnozernaya', a decrease in GQQ and PGQGQQ by one unit was revealed. In addition, substitutions of five amino acids were found in 'Leningradka krupnozernaya'. Thus, we have found previously undescribed deletions and substitutions in the nucleotide sequences of the Glu-B1-1 gene for high-molecular-weight glutenins, which lead to changes in amino acid sequences in functionally important regions, namely, in the central domains of protein molecules. The identified mutations can be used for genotyping bread wheat cultivars.

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.

Molecular Characterization and SNP-Based Molecular Marker Development of Two Novel High Molecular Weight Glutenin Genes from Triticum spelta L

Spelt wheat (Triticum spelta L., 2n=6x=42, AABBDD) is a valuable source of new gene resources for wheat genetic improvement. In the present study, two novel high molecular weight glutenin subunits (HMW-GS) 1Ax2.1* at Glu-A1 and 1By19* at Glu-B1 from German spelt wheat were identified. The encoding genes of both subunits were amplified and cloned by allele-specific PCR (AS-PCR), and the complete sequences of open reading frames (ORF) were obtained. 1Ax2.1* with 2478 bp and 1By19* with 2163 bp encoded 824 and 720 amino acid residues, respectively. Molecular characterization showed that both subunits had a longer repetitive region, and high percentage of α-helices at the N- and C-termini, which are beneficial for forming superior gluten macropolymers. Protein modelling by AlphaFold2 revealed similar three-diamensional (3D) structure features of 1Ax2.1* with two x-type superior quality subunits (1Ax1 and 1Ax2*) and 1By19* with four y-type superior quality subunits (1By16, 1By9, 1By8 and 1By18). Four cysteine residues in the three x-type subunits (1Ax2.1*, 1Ax1 and 1Ax2*) and the cysteine in intermediate repeat region of y-type subunits were not expected to participate in intramolecular disulfide bond formation, but these cysteines might form intermolecular disulfide bonds with other glutenins and gliadins to enhance gluten macropolymer formation. The SNP-based molecular markers for 1Ax2.1* and 1By19* genes were developed, which were verified in different F2 populations and recombination inbred lines (RILs) derived from crossing between spelt wheat and bread wheat cultivars. This study provides data on new glutenin genes and molecular markers for wheat quality improvement.

Quantitative traits loci mapping and molecular marker development for total glutenin and glutenin fraction contents in wheat

BACKGROUND

Glutenin contents and compositions are crucial factors influencing the end-use quality of wheat. Although the composition of glutenin fractions is well known, there has been relatively little research on the genetic basis of glutenin fractions in wheat.

RESULTS

To elucidate the genetic basis for the contents of glutenin and its fractions, a population comprising 196 recombinant inbred lines (RILs) was constructed from two parents, Luozhen No.1 and Zhengyumai 9987, which differ regarding their total glutenin and its fraction contents (except for the By fraction). Forty-one additive Quantitative Trait Loci (QTL) were detected in four environments over two years. These QTL explained 1.3% - 53.4% of the phenotypic variation in the examined traits. Forty-three pairs of epistatic QTL (E-QTL) were detected in the RIL population across four environments. The QTL controlling the content of total glutenin and its seven fractions were detected in clusters. Seven clusters enriched with QTL for more than three traits were identified, including a QTL cluster 6AS-3, which was revealed as a novel genetic locus for glutenin and related traits. Kompetitive Allele-Specific PCR (KASP) markers developed from the main QTL cluster 1DL-2 and the previously developed KASP marker for the QTL cluster 6AS-3 were validated as significantly associated with the target traits in the RIL population and in natural varieties.

CONCLUSIONS

This study identified novel genetic loci related to glutenin and its seven fractions. Additionally, the developed KASP markers may be useful for the marker-assisted selection of varieties with high glutenin fraction content and for identifying individuals in the early developmental stages without the need for phenotyping mature plants. On the basis of the results of this study and the KASP markers described herein, breeders will be able to efficiently select wheat lines with favorable glutenin properties and develop elite lines with high glutenin subunit contents.

Proteome and transcriptome analyses of wheat near isogenic lines identifies key proteins and genes of wheat bread quality

The regulation of wheat protein quality is a highly complex biological process involving multiple metabolic pathways. To reveal new insights into the regulatory pathways of wheat glutenin synthesis, we used the grain-filling period wheat grains of the near-isogenic lines NIL-723 and NIL-1010, which have large differences in quality, to perform a combined transcriptome and proteome analysis. Compared with NIL-1010, NIL-723 had 1287 transcripts and 355 proteins with significantly different abundances. Certain key significantly enriched pathway were identified, and wheat quality was associated with alanine, aspartate and glutamate metabolism, nitrogen metabolism and alpha-linolenic acid metabolism. Differentially expressed proteins (DEPs) or Differentially expressed genes (DEGs) in amino acid synthesis pathways were upregulated primarily in the glycine (Gly), methionine (Met), threonine (Thr), glutamic acid (Glu), proline (proC), cysteine (Cys), and arginine (Arg) synthesis and downregulated in the tryptophan (trpE), leucine (leuC), citrulline (argE), and ornithine (argE) synthesis. Furthermore, to elucidate changes in glutenin in the grain synthesis pathway, we plotted a regulatory pathway map and found that DEGs and DEPs in ribosomes (RPL5) and the ER (HSPA5, HYOU1, PDIA3, PDIA1, Sec24, and Sec31) may play key roles in regulating glutenin synthesis. The transcriptional validation of some of the differentially expressed proteins through real-time quantitative PCR analysis further validated the transcriptome and proteomic results.

Genetic Basis of Gluten Aggregation Properties in Wheat (Triticum aestivum L.) Dissected by QTL Mapping of GlutoPeak Parameters

Bread wheat is one of the most important crops worldwide, supplying approximately one-fifth of the daily protein and the calories for human consumption. Gluten aggregation properties play important roles in determining the processing quality of wheat (Triticum aestivum L.) products. Nevertheless, the genetic basis of gluten aggregation properties has not been reported so far. In this study, a recombinant inbred line (RIL) population derived from the cross between Luozhen No. 1 and Zhengyumai 9987 was used to identify quantitative trait loci (QTL) underlying gluten aggregation properties with GlutoPeak parameters. A linkage map was constructed based on 8,518 SNPs genotyped by specific length amplified fragment sequencing (SLAF-seq). A total of 33 additive QTLs on 14 chromosomes were detected by genome-wide composite interval mapping (GCIM), four of which accounted for more than 10% of the phenotypic variation across three environments. Two major QTL clusters were identified on chromosomes 1DS and 1DL. A premature termination of codon (PTC) mutation in the candidate gene (TraesCS1D02G009900) of the QTL cluster on 1DS was detected between Luozhen No. 1 and Zhengyumai 9987, which might be responsible for the difference in gluten aggregation properties between the two varieties. Subsequently, two KASP markers were designed based on SNPs in stringent linkage with the two major QTL clusters. Results of this study provide new insights into the genetic architecture of gluten aggregation properties in wheat, which are helpful for future improvement of the processing quality in wheat breeding.

Rapid and Easy High-Molecular-Weight Glutenin Subunit Identification System by Lab-on-a-Chip in Wheat (Triticum aestivum L.)

Lab-on-a-chip technology is an emerging and convenient system to easily and quickly separate proteins of high molecular weight. The current study established a high-molecular-weight glutenin subunit (HMW-GS) identification system using Lab-on-a-chip for three, six, and three of the allelic variations at the Glu-A1, Glu-B1, and Glu-D1 loci, respectively, which are commonly used in wheat breeding programs. The molecular weight of 1Ax1 and 1Ax2* encoded by Glu-A1 locus were of 200 kDa and 192 kDa and positioned below 1Dx subunits. The HMW-GS encoded by Glu-B1 locus were electrophoresed in the following order below 1Ax1 and 1Ax2*: 1Bx13 ≥ 1Bx7 = 1Bx7^OE > 1Bx17 > 1By16 > 1By8 = 1By18 > 1By9. 1Dx2 and Dx5 showed around 4-kDa difference in their molecular weights, with 1Dy10 and 1Dy12 having 11-kDa difference, and were clearly differentiated on Lab-on-a-chip. Additionally, some of the HMW-GS, including 1By8, 1By18, and 1Dy10, having different theoretical molecular weights showed similar electrophoretic mobility patterns on Lab-on-a-chip. The relative protein amount of 1Bx7^OE was two-fold higher than that of 1Bx7 or 1Dx5 and, therefore, translated a significant increase in the protein amount in 1Bx7^OE. Similarly, the relative protein amounts of 8 & 10 and 10 & 18 were higher than each subunit taken alone. Therefore, this study suggests the established HMW-GS identification system using Lab-on-a-chip as a reliable approach for evaluating HMW-GS for wheat breeding programs.

Economical optimization of a breeding scheme by selective phenotyping of the calibration set in a multi-trait context: application to bread making quality

Trait-assisted genomic prediction approach is a way to improve genetic gain by cost unit, by reducing budget allocated to phenotyping or by increasing the program's size for the same budget. This study compares different strategies of genomic prediction to optimize resource allocation in breeding schemes by using information from cheaper correlated traits to predict a more expensive trait of interest. We used bread wheat baking score (BMS) calculated for French registration as a case study. To conduct this project, 398 lines from a public breeding program were genotyped and phenotyped for BMS and correlated traits in 11 locations in France between 2000 and 2016. Single-trait (ST), multi-trait (MT) and trait-assisted (TA) strategies were compared in terms of predictive ability and cost. In MT and TA strategies, information from dough strength (W), a cheaper trait correlated with BMS (r = 0.45), was evaluated in the training population or in both the training and the validation sets, respectively. TA models allowed to reduce the budget allocated to phenotyping by up to 65% while maintaining the predictive ability of BMS. TA models also improved the predictive ability of BMS compared to ST models for a fixed budget (maximum gain: + 0.14 in cross-validation and + 0.21 in forward prediction). We also demonstrated that the budget can be further reduced by approximately one fourth while maintaining the same predictive ability by reducing the number of phenotypic records to estimate BMS adjusted means. In addition, we showed that the choice of the lines to be phenotyped can be optimized to minimize cost or maximize predictive ability. To do so, we extended the mean of the generalized coefficient of determination (CD_mean) criterion to the multi-trait context (CD_multi).

SNP markers for low molecular glutenin subunits (LMW-GSs) at the Glu-A3 and Glu-B3 loci in bread wheat

The content and composition of seed storage proteins is largely responsible for wheat end-use quality. They mainly consist of polymeric glutenins and monomeric gliadins. According to their electrophoretic mobility, gliadins and glutenins are subdivided into several fractions. Glutenins are classified as high molecular weight or low molecular weight glutenin subunits (HMW-GSs and LMW-GSs, respectively). LMW-GSs are encoded by multigene families located at the orthologous Glu-3 loci. We designed a set of 16 single-nucleotide polymorphism (SNP) markers that are able to detect SDS-PAGE alleles at the Glu-A3 and Glu-B3 loci. The SNP markers captured the diversity of alleles in 88 international reference lines and 27 Mexican cultivars, when compared to SDS-PAGE and STS markers, however, showed a slightly larger percent of multiple alleles, mainly for Glu-B3. SNP markers were then used to determine the Glu-1 and Glu-3 allele composition in 54 CIMMYT historical lines and demonstrated to be useful tool for breeding programs to improve wheat end product properties.