Identification of Fusarium Head Blight Resistance in Triticum timopheevii Accessions and Characterization of Wheat-T. timopheevii Introgression Lines for Enhanced Resistance

Chromosome-scale genome assembly of bread wheat's wild relative Triticum timopheevii

Wheat (Triticum aestivum) is one of the most important food crops with an urgent need for increase in its production to feed the growing world. Triticum timopheevii (2n = 4x = 28) is an allotetraploid wheat wild relative species containing the At and G genomes that has been exploited in many pre-breeding programmes for wheat improvement. In this study, we report the generation of a chromosome-scale reference genome assembly of T. timopheevii accession PI 94760 based on PacBio HiFi reads and chromosome conformation capture (Hi-C). The assembly comprised a total size of 9.35 Gb, featuring a contig N50 of 42.4 Mb and included the mitochondrial and plastid genome sequences. Genome annotation predicted 166,325 gene models including 70,365 genes with high confidence. DNA methylation analysis showed that the G genome had on average more methylated bases than the At genome. In summary, the T. timopheevii genome assembly provides a valuable resource for genome-informed discovery of agronomically important genes for food security.

Genome scans capture key adaptation and historical hybridization signatures in tetraploid wheat

Tetraploid wheats (Triticum turgidum L.), including durum wheat (T. turgidum ssp. durum (Desf.) Husn.), are important crops with high nutritional and cultural values. However, their production is constrained by sensitivity to environmental conditions. In search of adaptive genetic signatures tracing historical selection and hybridization events, we performed genome scans on two datasets: (1) Durum Global Diversity Panel comprising a total of 442 tetraploid wheat and wild progenitor accessions including durum landraces (n = 286), domesticated emmer (T. turgidum ssp. dicoccum (Schrank) Thell.; n = 103) and wild emmer (T. turgidum ssp. dicoccoides (Korn. ex Asch. & Graebn.) Thell.; n = 53) wheats genotyped using the 90K single nucleotide polymorphism (SNP) array, and (2) a second dataset comprising a total 121 accessions of nine T. turgidum subspecies including wild emmer genotyped with >100 M SNPs from whole-genome resequencing. The genome scan on the first dataset detected six outlier loci on chromosomes 1A, 1B, 3A (n = 2), 6A, and 7A. These loci harbored important genes for adaptation to abiotic stresses, phenological responses, such as seed dormancy, circadian clock, flowering time, and key yield-related traits, including pleiotropic genes, such as HAT1, KUODA1, CBL1, and ZFN1. The scan on the second dataset captured a highly differentiated region on chromosome 2B that shows significant differentiation between two groups: one group consists of Georgian (T. turgidum ssp. paleocolchicum A. Love & D. Love) and Persian (T. turgidum ssp. carthlicum (Nevski) A. Love & D. Love) wheat accessions, while the other group comprises all the remaining tetraploids including wild emmer. This is consistent with a previously reported introgression in this genomic region from T. timopheevii Zhuk. which naturally cohabit in the Georgian and neighboring areas. This region harbored several adaptive genes, including the thermomorphogenesis gene PIF4, which confers temperature-resilient disease resistance and regulates other biological processes. Genome scans can be used to fast-track germplasm housed in gene banks and in situ; which helps to identify environmentally resilient accessions for breeding and/or to prioritize them for conservation.

Comparative transcriptomic analysis of wheat cultivars differing in their resistance to Fusarium head blight infection during grain-filling stages reveals unique defense mechanisms at play

Fusarium head blight (FHB) is a devastating fungal disease that poses a significant threat to wheat production, causing substantial yield losses. Understanding the molecular mechanisms of wheat resistance to FHB is crucial for developing effective disease management strategies. This study aimed to investigate the mechanisms of FHB resistance and the patterns of toxin accumulation in three wheat cultivars, Annong8455, Annong1589, and Sumai3, with different levels of resistance, ranging from low to high respectively, under natural field conditions. Samples were taken at three different grain-filling stages (5, 10, and 15 DPA) for gene expression analysis and phenotypic observation. Results found that toxin concentration was inversely correlated with varietal resistance but not correlated with disease phenotypes, indicating that toxin analysis is a more accurate measure of disease status in wheat ears and grains. Transcriptomic data showed that Sumai3 exhibited a stronger immune response during all stages of grain filling by upregulating genes involved in the active destruction of pathogens and removal of toxins. In contrast, Annong1589 showed a passive prevention of the spread of toxins into cells by the upregulation of genes involved in tyramine biosynthesis at the early stage (5 DPA), which may be involved in cell wall strengthening. Our study demonstrates the complexity of FHB resistance in wheat, with cultivars exhibiting unique and overlapping defense mechanisms, and highlights the importance of considering the temporal and spatial dynamics of gene expression in breeding programs for developing more resistant wheat cultivars.

Metabolic Profiling Identifies Changes in the Winter Wheat Grains Following Fusarium Treatment at Two Locations in Croatia

Fusarium head blight (FHB) is one of the most dangerous diseases of winter wheat, resulting in reduced grain yield and quality, and production of mycotoxins by the Fusarium fungi. In the present study, changes in the grain metabolomics of winter wheat samples infected with Fusarium spp. and corresponding non-infected samples from two locations in Croatia were investigated by GC-MS. A Mann-Whitney test revealed that 24 metabolites detected were significantly separated between Fusarium-inoculated and non-infected samples during the variety by treatment interactions. The results confirmed that in grains of six FHB-resistant varieties, ten metabolites were identified as possible resistance-related metabolites. These metabolites included heptadecanoic acid, 9-(Z)-hexadecenoic acid, sophorose, and secolaganin in grains of FHB-resistant varieties at the Osijek location, as well as 2-methylaminomethyltartronic acid, maleamic acid, 4-hydroxyphenylacetonitrile, 1,4-lactonearabinonic acid, secolaganin, and alanine in grains of FHB-resistant varieties at the Tovarnik location. Moreover, on the PCA bi-plot, FHB-susceptible wheat varieties were closer to glycyl proline, decanoic acid, and lactic acid dimer that could have affected other metabolites, and thus, suppressed resistance to FHB. Although defense reactions were genetically conditioned and variety specific, resulting metabolomics changes may give insight into defense-related pathways that could be manipulated to engineer plants with improved resistance to the pathogen.

Phenotyping Fusarium head blight through seed morphology characteristics using RGB imaging

Fusarium head blight (FHB) is an economically important disease affecting wheat and thus poses a major threat to wheat production. Several studies have evaluated the effectiveness of image analysis methods to predict FHB using disease-infected grains; however, few have looked at the final application, considering the relationship between cost and benefit, resolution, and accuracy. The conventional screening of FHB resistance of large-scale samples is still dependent on low-throughput visual inspections. This study aims to compare the performance of two cost-benefit seed image analysis methods, the free software "SmartGrain" and the fully automated commercially available instrument "Cgrain Value™" by assessing 16 seed morphological traits of winter wheat to predict FHB. The analysis was carried out on a seed set of FHB which was visually assessed as to the severity. The dataset is composed of 432 winter wheat genotypes that were greenhouse-inoculated. The predictions from each method, in addition to the predictions combined from the results of both methods, were compared with the disease visual scores. The results showed that Cgrain Value™ had a higher prediction accuracy of R ² = 0.52 compared with SmartGrain for which R ² = 0.30 for all morphological traits. However, the results combined from both methods showed the greatest prediction performance of R ² = 0.58. Additionally, a subpart of the morphological traits, namely, width, length, thickness, and color features, showed a higher correlation with the visual scores compared with the other traits. Overall, both methods were related to the visual scores. This study shows that these affordable imaging methods could be effective to predict FHB in seeds and enable us to distinguish minor differences in seed morphology, which could lead to a precise performance selection of disease-free seeds/grains.