From farm to fork: future supply chains need to measure and trade nutrient content.

In the future, 8-10 billion people will need to be fed by our agriculture and food production system. Moreover, currently up to five billion people are already affected by malnutrition including undernutrition, inadequate consumption of micronutrients, and overweight. A healthy and sustainable diet will therefore play a pivotal role in our future, but most food products are traded and consumed based only on techno-functional or gustatory properties. We wish to stimulate a debate on the urgent need for multidisciplinary research and education to realize future diets with enhanced nutritional profiles. In particular, there is a need to better measure and understand the factors that influence the nutrients of food products along the global supply chains.

Multiomics Based Association Mapping in Wheat Reveals Genetic Architecture of Quality and Allergenic Related Proteins.

Wheat is an important staple crop since its proteins contribute to human and animal nutrition and are important for its end-use quality. However, wheat proteins can also cause adverse human reactions for a large number of people. We performed a genome wide association study (GWAS) on 114 proteins quantified by LC-MS-based proteomics and expressed in an environmentally stable manner in 148 wheat cultivars with a heritability > 0.6. For 54 proteins, we detected quantitative trait loci (QTL) that exceeded the Bonferroni-corrected significance threshold and explained 17.3−84.5% of the genotypic variance. Proteins in the same family often clustered at a very close chromosomal position or the potential homeolog. Major QTLs were found for four well-known glutenin and gliadin subunits, and the QTL segregation pattern in the protein encoding the high molecular weight glutenin subunit Dx5 could be confirmed by SDS gel-electrophoresis. For nine potential allergenic proteins, large QTLs could be identified, and their measured allele frequencies open the possibility to select for low protein abundance by markers as long as their relevance for human health has been conclusively demonstrated. A potential allergen was introduced in the beginning of 1980s that may be linked to the cluster of resistance genes introgressed on chromosome 2AS from Triticum ventricosum. The reported sequence information for the 54 major QTLs can be used to design efficient markers for future wheat breeding.

Capturing Wheat Phenotypes at the Genome Level.

Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world's most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public-private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.

Genetic architecture underlying the expression of eight α-amylase trypsin inhibitors.

KEY MESSAGE: Wheat cultivars largely differ in the content and composition of ATI proteins, but heritability was quite low for six out of eight ATIs. The genetic architecture of ATI proteins is built up of few major and numerous small effect QTL. Amylase trypsin inhibitors (ATIs) are important allergens in baker's asthma and suspected triggers of non-celiac wheat sensitivity (NCWS) inducing intestinal and extra-intestinal inflammation. As studies on the expression and genetic architecture of ATI proteins in wheat are lacking, we evaluated 149 European old and modern bread wheat cultivars grown at three different field locations for their content of eight ATI proteins. Large differences in the content and composition of ATIs in the different cultivars were identified ranging from 3.76 pmol for ATI CM2 to 80.4 pmol for ATI 0.19, with up to 2.5-fold variation in CM-type and up to sixfold variation in mono/dimeric ATIs. Generally, heritability estimates were low except for ATI 0.28 and ATI CM2. ATI protein content showed a low correlation with quality traits commonly analyzed in wheat breeding. Similarly, no trends were found regarding ATI content in wheat cultivars originating from numerous countries and decades of breeding history. Genome-wide association mapping revealed a complex genetic architecture built of many small, few medium and two major quantitative trait loci (QTL). The major QTL were located on chromosomes 3B for ATI 0.19-like and 6B for ATI 0.28, explaining 70.6 and 68.7% of the genotypic variance, respectively. Within close physical proximity to the medium and major QTL, we identified eight potential candidate genes on the wheat reference genome encoding structurally related lipid transfer proteins. Consequently, selection and breeding of wheat cultivars with low ATI protein amounts appear difficult requiring other strategies to reduce ATI content in wheat products.

Characterization of 150 Wheat Cultivars by LC-MS-Based Label-Free Quantitative Proteomics Unravels Possibilities to Design Wheat Better for Baking Quality and Human Health.

Wheat (Triticum aestivum ssp. aestivum) contributes to 20% of the human protein supply, delivers essential amino acids and is of fundamental importance for bread and pasta quality. Wheat proteins are also involved in adverse human reactions like celiac disease (CD), wheat allergy (WA) and non-celiac wheat sensitivity (NCWS). Using liquid chromatography-mass spectrometry (LC-MS)-based label-free quantitative (LFQ) proteomics of aqueous flour extracts, we determined 756 proteins across 150 wheat cultivars grown in three environments. However, only 303 proteins were stably expressed across all environments in at least one cultivar and only 89 proteins thereof across all 150 cultivars. This underlines the large influence of environmental conditions on the expression of many proteins. Wheat cultivars varied largely in their protein profile, shown by high coefficients of variation across different cultivars. Heritability (h2) ranged from 0-1, with 114 proteins having h² > 0.6, including important proteins for baking quality and human health. The expression of these 114 proteins should be amenable to targeted manipulation across the wheat supply chain by varietal choice and breeding for designing healthier wheat with better quality. Further technical development is urgently required to assign functions to identifiable proteins labeled yet uncharacterized in databases and speeding up detection methods to routinely use proteomics in wheat supply chains.

Hybrid QconCAT-Based Targeted Absolute and Data-Independent Acquisition-Based Label-Free Quantification Enables In-Depth Proteomic Characterization of Wheat Amylase/Trypsin Inhibitor Extracts.

Wheat amylase/trypsin inhibitors (ATIs) have gained significant relevance as inducers of intestinal and extra-intestinal inflammation. In this study, we present a novel hybrid data-independent acquisition (DIA) liquid chromatography-mass spectrometry (LC-MS) approach, combining QconCAT technology with short microflow LC gradients and DIA and apply the method toward the quantitative proteome analysis of ATI extracts. The presented method is fast, robust, and reproducible and provides precise QconCAT-based absolute quantification of major ATI proteins while simultaneously quantifying the proteome by label-free quantification (LFQ). We analyzed extracts of 60 varieties of common wheat grown in replication and evaluated the reproducibility and precision of the workflow for the quantification of ATIs. Applying the method to analyze different wheat species (i.e., common wheat, spelt, durum wheat, emmer, and einkorn) and comparing the results to published data, we validated inter-laboratory and cross-methodology reproducibility of ATI quantification, which is essential in the context of large-scale breeding projects. Additionally, we applied our workflow to assess environmental effects on ATI expression, analyzing ATI content and proteome of same varieties grown at different locations. Finally, we explored the potential of combining QconCAT-based absolute quantification with DIA-based LFQ proteome analysis for the generation of new hypotheses or assay development.

Genomic Regions Associated with the Control of Flowering Time in Durum Wheat.

Flowering time is a critical stage for crop development as it regulates the ability of plants to adapt to an environment. To understand the genetic control of flowering time, a genome-wide association study (GWAS) was conducted to identify the genomic regions associated with the control of this trait in durum wheat (Triticum durum Desf.). A total of 96 landraces and 288 modern lines were evaluated for days to heading, growing degree days, and accumulated day length at flowering across 13 environments spread across Morocco, Lebanon, Mauritania, and Senegal. These environments were grouped into four pheno-environments based on temperature, day length, and other climatic variables. Genotyping with a 35K Axiom array generated 7652 polymorphic single nucleotide polymorphisms (SNPs) in addition to 3 KASP markers associated with known flowering genes. In total, 32 significant QTLs were identified in both landraces and modern lines. Some QTLs had a strong association with already known regulatory photoperiod genes, Ppd-A and Ppd-B, and vernalization genes Vrn-A1 and VrnA7. However, these loci explained only 5% to 20% of variance for days to heading. Seven QTLs overlapped between the two germplasm groups in which Q.ICD.Eps-03 and Q.ICD.Vrn-15 consistently affected flowering time in all the pheno-environments, while Q.ICD.Eps-09 and Q.ICD.Ppd-10 were significant only in two pheno-environments and the combined analysis across all environments. These results help clarify the genetic mechanism controlling flowering time in durum wheat and show some clear distinctions to what is known for common wheat (Triticum aestivum L.).

A Major Root Architecture QTL Responding to Water Limitation in Durum Wheat.

The optimal root system architecture (RSA) of a crop is context dependent and critical for efficient resource capture in the soil. Narrow root growth angle promoting deeper root growth is often associated with improved access to water and nutrients in deep soils during terminal drought. RSA, therefore is a drought-adaptive trait that could minimize yield losses in regions with limited rainfall. Here, GWAS for seminal root angle (SRA) identified seven marker-trait associations clustered on chromosome 6A, representing a major quantitative trait locus (qSRA-6A) which also displayed high levels of pairwise LD (r 2 = 0.67). Subsequent haplotype analysis revealed significant differences between major groups. Candidate gene analysis revealed loci related to gravitropism, polar growth and hormonal signaling. No differences were observed for root biomass between lines carrying hap1 and hap2 for qSRA-6A, highlighting the opportunity to perform marker-assisted selection for the qSRA-6A locus and directly select for wide or narrow RSA, without influencing root biomass. Our study revealed that the genetic predisposition for deep rooting was best expressed under water-limitation, yet the root system displayed plasticity producing root growth in response to water availability in upper soil layers. We discuss the potential to deploy root architectural traits in cultivars to enhance yield stability in environments that experience limited rainfall.