Proteomic Data Integration Highlights Central Actors Involved in Einkorn (Triticum monococcum ssp. monococcum) Grain Filling in Relation to Grain Storage Protein Composition

Breeding for Economically and Environmentally Sustainable Wheat Varieties: An Integrated Approach from Genomics to Selection

There is currently a strong societal demand for sustainability, quality, and safety in bread wheat production. To address these challenges, new and innovative knowledge, resources, tools, and methods to facilitate breeding are needed. This starts with the development of high throughput genomic tools including single nucleotide polymorphism (SNP) arrays, high density molecular marker maps, and full genome sequences. Such powerful tools are essential to perform genome-wide association studies (GWAS), to implement genomic and phenomic selection, and to characterize the worldwide diversity. This is also useful to breeders to broaden the genetic basis of elite varieties through the introduction of novel sources of genetic diversity. Improvement in varieties particularly relies on the detection of genomic regions involved in agronomical traits including tolerance to biotic (diseases and pests) and abiotic (drought, nutrient deficiency, high temperature) stresses. When enough resolution is achieved, this can result in the identification of candidate genes that could further be characterized to identify relevant alleles. Breeding must also now be approached through in silico modeling to simulate plant development, investigate genotype × environment interactions, and introduce marker-trait linkage information in the models to better implement genomic selection. Breeders must be aware of new developments and the information must be made available to the world wheat community to develop new high-yielding varieties that can meet the challenge of higher wheat production in a sustainable and fluctuating agricultural context. In this review, we compiled all knowledge and tools produced during the BREEDWHEAT project to show how they may contribute to face this challenge in the coming years.

Biostimulant impacts of Glutacetine® and derived formulations (VNT1 and VNT4) on the bread wheat grain proteome

Nitrogen (N) fertilizer is essential to ensure grain yield and quality in bread wheat. Improving N use efficiency is therefore crucial for wheat grain protein quality. In the present work, we analysed the effects on the winter wheat grain proteome of biostimulants containing Glutacetine® or two derived formulations (VNT1 and 4) when mixed with urea-ammonium-nitrate fertilizer. A large-scale quantitative proteomics analysis of two wheat flour fractions produced a dataset of 4369 identified proteins. Quantitative analysis revealed 9, 39 and 96 proteins with a significant change in abundance after Glutacetine®, VNT1 and VNT4 treatments, respectively, with a common set of 11 proteins that were affected by two different biostimulants. The major effects impacted proteins involved in (i) protein synthesis regulation (mainly ribosomal and binding proteins), (ii) defence and responses to stresses (including chitin-binding protein, heat shock 70 kDa protein 1 and glutathione S-transferase proteins), (iii) storage functions related to gluten protein alpha-gliadins and starch synthase and (iv) seed development with proteins implicated in protease activity, energy machinery, and the C and N metabolism pathways. Altogether, our study showed that Glutacetine®, VNT1 and VNT4 biostimulants positively affected protein composition related to grain quality. Data are available via ProteomeXchange with identifier PXD021513. SIGNIFICANCE: We performed a large-scale quantitative proteomics study of the total protein extracts from flour samples to determine the effect of Glutacetine®-based biostimulants treatment on the protein composition of bread wheat grain. To our knowledge, only a few studies in the literature have applied proteomic approaches to study bread wheat grains and in particular to investigate the effect of biostimulants on the grain proteome of this cereal crop. In addition, most approaches used fractional extraction of proteins to target reserve proteins followed electrophoresis which leads to low identification rate of proteins. We identified and quantified a large protein dataset of 4369 proteins and determined ontological class of proteins affected by biostimulants treatments. Our proteomics investigation revealed the important role of these new biostimulants in achieving significant changes in protein synthesis regulation, storage functions, protease activity, energy machinery, C and N metabolism pathways and responses to biotic and abiotic stresses in grain.