Capturing Wheat Phenotypes at the Genome Level

Breeding in bread-making wheat varieties for Mediterranean climate: the need to get resilient varieties

Introduction

Being one of the "big three" most cultivated cereals in the world, wheat plays a crucial role in ensuring global food/nutrition security, supplying close to 20% of the global needs for calories and proteins. However, the increasingly large fluctuations between years in temperatures and precipitation due to climate change cause important variations in wheat production worldwide. This fact makes wheat breeding programs a tool that, far from going out of fashion, is becoming the most important solution to develop varieties that can provide humanity with the sufficient amount of food it demands without forgetting the objective of quality.

Material and methods

The National Institute of Agricultural and Veterinary Research in Portugal has carried out a long-term experiment (9 years) in different locations to test four different bread-making wheat cultivars, each representing important variations in germplasm. Wheat yield and quality traits obtained by official methods were recorded in 18 different environments regarding temperature and precipitation.

Results and discussion

According to the ANOVA and PCA, protein content, wet gluten, dough tenacity, and extensibility were found to be highly affected by the environment. Paiva cultivar presented a higher yield in almost all the tested environments, but its quality traits varied enormously. Contrary behavior was recorded for Valbona cultivar. Antequera cultivar, with a production ranging between 4.7 and 9.3 tons/ha and a protein content between 11 and 16.8%, seems to be the most resilient cultivar regarding both productivity and quality of the flour with reference to changes in the main climate traits. The most ancient cultivar, Roxo, released in 1996, showed the worst results in this experiment, supporting the need to continue working in wheat breeding to meet the unavoidable changes in the environment.

Community Resource: Large-Scale Proteogenomics to Refine Wheat Genome Annotations

Triticum aestivum is an important crop whose reference genome (International Wheat Genome Sequencing Consortium (IWGSC) RefSeq v2.1) offers a valuable resource for understanding wheat genetic structure, improving agronomic traits, and developing new cultivars. A key aspect of gene model annotation is protein-level evidence of gene expression obtained from proteomics studies, followed up by proteogenomics to physically map proteins to the genome. In this research, we have retrieved the largest recent wheat proteomics datasets publicly available and applied the Basic Local Alignment Search Tool (tBLASTn) algorithm to map the 861,759 identified unique peptides against IWGSC RefSeq v2.1. Of the 92,719 hits, 83,015 unique peptides aligned along 33,612 High Confidence (HC) genes, thus validating 31.4% of all wheat HC gene models. Furthermore, 6685 unique peptides were mapped against 3702 Low Confidence (LC) gene models, and we argue that these gene models should be considered for HC status. The remaining 2934 orphan peptides can be used for novel gene discovery, as exemplified here on chromosome 4D. We demonstrated that tBLASTn could not map peptides exhibiting mid-sequence frame shift. We supply all our proteogenomics results, Galaxy workflow and Python code, as well as Browser Extensible Data (BED) files as a resource for the wheat community via the Apollo Jbrowse, and GitHub repositories. Our workflow could be applied to other proteomics datasets to expand this resource with proteins and peptides from biotically and abiotically stressed samples. This would help tease out wheat gene expression under various environmental conditions, both spatially and temporally.

Characterization of Pre-Breeding Wheat (Triticum aestivum L.) Germplasm for Stripe Rust Resistance Using Field Phenotyping and Genotyping

Wheat is highly affected by stripe rust disease, particularly under cooler environments, and the losses can reach up to 100 percent depending on the intensity of infection and the susceptibility of the genotype. The most effective method to manage this disease is the use of resistant varieties. In the present study, 192 wheat genotypes were evaluated for stripe rust resistance under field conditions and also in a laboratory using molecular markers. These lines included pre-breeding germplasm developed for rust resistance and some high-yielding commercially grown wheat varieties. Out of 192 genotypes, 53 were found to be resistant, and 29 showed moderate resistance reaction under field conditions, whereas the remaining genotypes were all either moderately susceptible or susceptible. Under controlled conditions, out of 109 genotypes, only 12 were found to be resistant to all the six virulent/pathogenic pathotypes. Additionally, a selection of 97 genotypes were found resistant in field screening and were subjected to molecular validation using the markers linked to major R-genes, viz., Yr5, Yr10, Yr15 and Yr17. Nine genotypes possessed the Yr5 gene, twelve had the Yr10 gene, fourteen had the Yr15 gene and thirty-two had the Yr17 gene. The resistance genes studied in the current study are effective in conferring resistance against stripe rust disease. The genotypes identified as resistant under both field and controlled conditions can be used as sources in stripe rust resistance breeding programs.

Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses

The present day's ongoing global warming and climate change adversely affect plants through imposing environmental (abiotic) stresses and disease pressure. The major abiotic factors such as drought, heat, cold, salinity, etc., hamper a plant's innate growth and development, resulting in reduced yield and quality, with the possibility of undesired traits. In the 21st century, the advent of high-throughput sequencing tools, state-of-the-art biotechnological techniques and bioinformatic analyzing pipelines led to the easy characterization of plant traits for abiotic stress response and tolerance mechanisms by applying the 'omics' toolbox. Panomics pipeline including genomics, transcriptomics, proteomics, metabolomics, epigenomics, proteogenomics, interactomics, ionomics, phenomics, etc., have become very handy nowadays. This is important to produce climate-smart future crops with a proper understanding of the molecular mechanisms of abiotic stress responses by the plant's genes, transcripts, proteins, epigenome, cellular metabolic circuits and resultant phenotype. Instead of mono-omics, two or more (hence 'multi-omics') integrated-omics approaches can decipher the plant's abiotic stress tolerance response very well. Multi-omics-characterized plants can be used as potent genetic resources to incorporate into the future breeding program. For the practical utility of crop improvement, multi-omics approaches for particular abiotic stress tolerance can be combined with genome-assisted breeding (GAB) by being pyramided with improved crop yield, food quality and associated agronomic traits and can open a new era of omics-assisted breeding. Thus, multi-omics pipelines together are able to decipher molecular processes, biomarkers, targets for genetic engineering, regulatory networks and precision agriculture solutions for a crop's variable abiotic stress tolerance to ensure food security under changing environmental circumstances.

Wheat Omics: Advancements and Opportunities

Plant omics, which includes genomics, transcriptomics, metabolomics and proteomics, has played a remarkable role in the discovery of new genes and biomolecules that can be deployed for crop improvement. In wheat, great insights have been gleaned from the utilization of diverse omics approaches for both qualitative and quantitative traits. Especially, a combination of omics approaches has led to significant advances in gene discovery and pathway investigations and in deciphering the essential components of stress responses and yields. Recently, a Wheat Omics database has been developed for wheat which could be used by scientists for further accelerating functional genomics studies. In this review, we have discussed various omics technologies and platforms that have been used in wheat to enhance the understanding of the stress biology of the crop and the molecular mechanisms underlying stress tolerance.

A community resource to mass explore the wheat grain proteome and its application to the late-maturity alpha-amylase (LMA) problem

BACKGROUND

Late-maturity alpha-amylase (LMA) is a wheat genetic defect causing the synthesis of high isoelectric point alpha-amylase following a temperature shock during mid-grain development or prolonged cold throughout grain development, both leading to starch degradation. While the physiology is well understood, the biochemical mechanisms involved in grain LMA response remain unclear. We have applied high-throughput proteomics to 4,061 wheat flours displaying a range of LMA activities. Using an array of statistical analyses to select LMA-responsive biomarkers, we have mined them using a suite of tools applicable to wheat proteins.

RESULTS

We observed that LMA-affected grains activated their primary metabolisms such as glycolysis and gluconeogenesis; TCA cycle, along with DNA- and RNA- binding mechanisms; and protein translation. This logically transitioned to protein folding activities driven by chaperones and protein disulfide isomerase, as well as protein assembly via dimerisation and complexing. The secondary metabolism was also mobilized with the upregulation of phytohormones and chemical and defence responses. LMA further invoked cellular structures, including ribosomes, microtubules, and chromatin. Finally, and unsurprisingly, LMA expression greatly impacted grain storage proteins, as well as starch and other carbohydrates, with the upregulation of alpha-gliadins and starch metabolism, whereas LMW glutenin, stachyose, sucrose, UDP-galactose, and UDP-glucose were downregulated.

CONCLUSIONS

To our knowledge, this is not only the first proteomics study tackling the wheat LMA issue but also the largest plant-based proteomics study published to date. Logistics, technicalities, requirements, and bottlenecks of such an ambitious large-scale high-throughput proteomics experiment along with the challenges associated with big data analyses are discussed.

Identification and validation of quantitative trait loci for chlorophyll content of flag leaf in wheat under different phosphorus treatments

In wheat, the leaf chlorophyll content in flag leaves is closely related to the degree of phosphorus stress. Identifying major genes/loci associated with chlorophyll content in flag leaves under different phosphorus conditions is critical for breeding wheat varieties resistant to low phosphorus (P). Under normal, medium, and low phosphorus conditions, the chlorophyll content of flag leaves was investigated by a double haploid (DH) population derived from a cross between two popular wheat varieties Jinmai 47 and Jinmai 84, at different grain filling stages. Chlorophyll content of the DH population and parents decreased gradually during the S1 to the S3 stages and rapidly at the S4 stage. At the S4 stage, the chlorophyll content of the DH population under low phosphorus conditions was significantly lower than under normal phosphate conditions. Using a wheat 15K single-nucleotide polymorphism (SNP) panel, a total of 157 QTLs were found to be associated with chlorophyll content in flag leaf and were identified under three phosphorus conditions. The phenotypic variation explained (PVE) ranged from 3.07 to 31.66%. Under three different phosphorus conditions, 36, 30, and 48 QTLs for chlorophyll content were identified, respectively. Six major QTLs Qchl.saw-2B.1, Qchl.saw-3B.1, Qchl.saw-4D.1, Qchl.saw-4D.2, Qchl.saw-5A.9 and Qchl.saw-6A.4 could be detected under multiple phosphorus conditions in which Qchl.saw-4D.1, Qchl.saw-4D.2, and Qchl.saw-6A.4 were revealed to be novel major QTLs. Moreover, the closely linked SNP markers of Qchl.saw-4D.1 and Qchl.saw-4D.2 were validated as KASP markers in a DH population sharing the common parent Jinmai 84, showed extreme significance (P <0.01) in more than three environments under different phosphorus conditions, which has the potential to be utilized in molecular marker-assisted breeding for low phosphorus tolerance in wheat.

Evaluation of grain yield performance and its stability in various spring barley accessions under condition of different agroclimatic zones of Ukraine

Two extremely urgent problems of biological and agronomic research nowadays are ensuring an optimal balance between usage of natural resources to meet rapidly growing needs for food production and preservation of biodiversity. It is also important to extend the genetic diversity of the main crop varieties in agroecosystems. At the same time, modern varieties should be characterized by a combination of high yield and preserving yield stability under variable conditions. Solving the outlined tasks requires comprehensive research and involvement in breeding process of the genetical diversity concentrated in genebanks of the world. Barley (Hordeum vulgare L.) is one of the most important crops that satisfy the various needs of humanity. In respect to this, in 2020–2022, a multi-environment trial was conducted in three agroclimatic zones of Ukraine (Forest-Steppe, Polissia, and Northern Steppe). We studied 44 spring barley collection accessions of different ecological and geographical origin, different subspecies and groups of botanical varieties which were obtained from the National Center for Plant Genetic Resources of Ukraine. Statistical indices (Hom, Sc) and graphical models (GGE biplot, AMMI) were used to interpret the yield performance and its stability. Both individual ecological sites in different years and combinations of different sites and years of trials were characterized for productivity, discriminating power and representativeness. The environments differed quite strongly among themselves in terms of these indicators. It was established that most of the genotypes were characterized by higher adaptability to individual environmental conditions (stability in different years), compared to adaptability for all agroclimatic zones (wide adaptation). A strong cross-over genotype by environment interaction was found for most studied accessions. Nevertheless, both genotypes with very high stability in only one agroclimatic zone (Amil (UKR), Gateway (CAN)) and genotypes with a combination of high adaptability to one or two ecological niches and relatively higher wide adaptability (Stymul (UKR), Ly-1064 (UKR), Rannij (KAZ), Shedevr (UKR), and Arthur (CZE)) were identified. There were also the accessions which did not show maximum performance in the individual sites, but had relatively higher wide adaptability (Ly-1059 (UKR), Ly-1120 (UKR), Diantus (UKR), and Danielle (CZE)). In general, the naked barley genotypes were inferior to the covered ones in terms of yield potential and wide adaptability, but at the same time, some of them (CDC ExPlus (CAN), CDC Gainer (CAN), and Roseland (CAN)), accordingly to the statistical indicators, had increased stability in certain ecological sites. Among naked barley accessions relatively better wide adaptability according to the graphical analysis was found in the accession CDC McGwire (CAN), and by the statistical parameters CDC ExPlus (CAN) was better than standard. The peculiarities of yield manifestation and its variability in different spring barley genotypes in the multi-environment trial revealed in this study will contribute to the complementation and deepening of existing data in terms of the genotype by environment interaction. Our results can be used in further studies for developing spring barley variety models both with specific and wide adaptation under conditions of different agroclimatic zones of Ukraine. The disitnguished accessions of different origin and botanical affiliation are recommended for creating a new breeding material with the aim of simultaneously increasing yield potential and stability, as well as widening the genetic basis of spring barley varieties.