Improving the baking quality of bread wheat using rapid tests and genomics: The prediction of dough rheological parameters by gluten peak indices and genomic selection models

Transcriptome Analysis Reveals Potential Mechanism in Storage Protein Trafficking within Developing Grains of Common Wheat

Gluten proteins are the major storage protein fraction in the mature wheat grain. They are restricted to the starchy endosperm, which defines the viscoelastic properties of wheat dough. The synthesis of these storage proteins is controlled by the endoplasmic reticulum (ER) and is directed into the vacuole via the Golgi apparatus. In the present study, transcriptome analysis was used to explore the potential mechanism within critical stages of grain development of wheat cultivar "Shaannong 33" and its sister line used as the control (CK). Samples were collected at 10 DPA (days after anthesis), 14 DPA, 20 DPA, and 30 DPA for transcriptomic analysis. The comparative transcriptome analysis identified that a total of 18,875 genes were differentially expressed genes (DEGs) between grains of four groups "T10 vs. CK10, T14 vs. CK14, T20 vs. CK20, and T30 vs. CK30", including 2824 up-regulated and 5423 down-regulated genes in T30 vs. CK30. Further, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment highlighted the maximum number of genes regulating protein processing in the endoplasmic reticulum (ER) during grain enlargement stages (10-20 DPA). In addition, KEGG database analysis reported 1362 and 788 DEGs involved in translation, ribosomal structure, biogenesis, flavonoid biosynthesis pathway and intracellular trafficking, secretion, and vesicular transport through protein processing within ER pathway (ko04141). Notably, consistent with the higher expression of intercellular storage protein trafficking genes at the initial 10 DPA, there was relatively low expression at later stages. Expression levels of nine randomly selected genes were verified by qRT-PCR, which were consistent with the transcriptome data. These data suggested that the initial stages of "cell division" played a significant role in protein quality control within the ER, thus maintaining the protein quality characteristics at grain maturity. Furthermore, our data suggested that the protein synthesis, folding, and trafficking pathways directed by a different number of genes during the grain enlargement stage contributed to the observed high-quality characteristics of gluten protein in Shaannong 33 (Triticum aestivum L.).

Promoter DNA hypermethylation of TaGli-γ-2.1 positively regulates gluten strength in bread wheat

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TaGli-γ-2.1 belonged to a subgroup of γ-gliadin multigene family.

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TaGli-γ-2.1 was a negative regulatory factor in gluten strength.

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Methylation of pTaGli-γ-2.1 played a key role in regulating TaGli-γ-2.1 expression.

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Lower γ-gliadin content followed with hypermethylation of pTaGli-γ-2.1.

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Decreasing TaGli-γ-2.1 expression could be used to improve gluten strength in wheat breeding.

Introduction

Gliadins are the major components of gluten proteins with vital roles on properties of end-use wheat product and health-relate quality of wheat. However, the function and regulation mechanisms of γ-gliadin genes remain unclear.

Objectives

Dissect the effect of DNA methylation in the promoter of γ-gliadin gene on its expression level and gluten strength of wheat.

Methods

The prokaryotic expression and reduction–oxidation reactions were performed to identify the effect of TaGli-γ-2.1 on dough strength. Bisulfite analysis and 5-Aza-2′-deoxycytidine treatment were used to verify the regulation of TaGli-γ-2.1 expression by pTaGli-γ-2.1 methylation. The content of gluten proteins composition was measured by RP-HPLC, and the gluten strength was measured by Gluten Index and Farinograph.

Results

TaGli-γ-2.1 was classified into a subgroup of γ-gliadin multigene family and was preferentially expressed in the later period of grain filling. Addition of TaGli-γ-2.1 protein fragment into strong gluten wheat flour significantly decreased the stability time. Hypermethylation of three CG loci of pTaGli-γ-2.1 conferred to lower TaGli-γ-2.1 expression. Treatment with 5-Aza-2′-deoxycytidine in seeds of strong gluten wheat varieties increased the expression levels of TaGli-γ-2.1. Furthermore, the accumulations of gliadin and γ-gliadin were significantly decreased in hypermethylated wheat varieties, corresponding with the increasing of gluten index and dough stability time.

Conclusion

Epigenetic modification of pTaGli-γ-2.1 affected gluten strength by modulating the proportion of gluten proteins. Hypermethylation of pTaGli-γ-2.1 is a novel genetic resource for enhancing gluten strength in wheat quality breeding.

An Overview of Key Factors Affecting Genomic Selection for Wheat Quality Traits

Selection for wheat (Triticum aestivum L.) grain quality is often costly and time-consuming since it requires extensive phenotyping in the last phases of development of new lines and cultivars. The development of high-throughput genotyping in the last decade enabled reliable and rapid predictions of breeding values based only on marker information. Genomic selection (GS) is a method that enables the prediction of breeding values of individuals by simultaneously incorporating all available marker information into a model. The success of GS depends on the obtained prediction accuracy, which is influenced by various molecular, genetic, and phenotypic factors, as well as the factors of the selected statistical model. The objectives of this article are to review research on GS for wheat quality done so far and to highlight the key factors affecting prediction accuracy, in order to suggest the most applicable approach in GS for wheat quality traits.

Effectiveness of Genomic Selection by Response to Selection for Winter Wheat Variety Improvement

Prediction performance for winter wheat grain yield and end-use quality traits. Prediction accuracies evaluated by cross-validations are significantly overestimated. Nonparametric algorithms outperform the parametric alternatives in cross-year predictions. Strategically designing training population improves response to selection. Response to selection varies across growing seasons and environments. Considering the practicality of applying genomic selection (GS) in the line development stage of a hard red winter (HRW) wheat (Triticum aestivum L.) variety development program (VDP), the effectiveness of GS was evaluated by prediction accuracy and by the response to selection across field seasons that demonstrated challenges for crop improvement under significant climate variability. Important breeding targets for wheat improvement in the southern Great Plains of the United States, including grain yield, kernel weight, wheat protein content, and sodium dodecyl sulfate (SDS) sedimentation volume as a rapid test for predicting bread-making quality, were used to estimate the effectiveness of GS across harvest years from 2014 (drought) to 2016 (normal). In general, nonparametric algorithms reproducing kernel Hilbert space (RKHS) and random forest (RF) produced higher accuracies in both same-year cross-validations (CVs) and cross-year predictions for the purpose of line selection. Further, the stability of GS performance was greatest for SDS sedimentation volume but least for wheat protein content. To ensure long-term genetic gain, our study on selection response suggested that across this sample of environmental variability, and though there are cases where phenotypic selection (PS) might be still preferred, training conducted under drought or in suboptimal conditions could provide an encouraging prediction outcome when selection decisions were made in normal conditions. However, it is not advisable to use training information collected from a normal season to predict trait performance under drought conditions. Finally, the superiority of response to selection was most evident if the training population (TP) can be optimized.

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.

Perspective on Wheat Yield and Quality with Reduced Nitrogen Supply

Wheat is an important cereal crop with a high demand for nitrogen (N) fertilizer to enable the grain protein accumulation that is necessary for baking and processing quality. Here, perspectives for the development of improved wheat genotypes with higher yield stability, better grain quality, and improved N use efficiency to lower environmental impacts are discussed. The development of improved wheat genotypes, for example, genotypes that lack storage proteins that do not contribute to baking quality (e.g., by genome editing), in combination with appropriate N fertilizer management to prevent N losses into the environment underpins a novel approach to improving N use efficiency. This approach may be particularly applicable to wheats grown for animal feed, which have lower quality and functionality requirements.