Fiona Leigh

Key message: Synthetic hexaploid wheat harbours STB resistance-associated loci with multi-isolate and isolate-specific effects, with partly independent genetic control of pycnidia suppression and necrosis. Septoria tritici blotch (STB), caused by Zymoseptoria tritici , is a major constraint on wheat production. Erosion of host resistance and declining fungicide efficacy highlight the need to exploit new resistance sources, including synthetic hexaploid wheat (SHW). We used a three-family nested association mapping (NAM) population derived from Niab SHW donors (SHW.035, SHW.054, and SHW.075) crossed with the UK variety Robigus to dissect the genetic basis of STB resistance under controlled conditions. Seedlings were challenged with five UK Z. tritici isolates differing in virulence, and disease progress was quantified separately as necrosis (AUDPC_N) and pycnidia coverage (AUDPC_P). Many SHW-derived lines showed strong suppression of pycnidia despite visible necrosis, consistent with partial genetic decoupling of pathogen reproduction and host tissue damage. GWAS identified a major multi-isolate association on chromosome 3D ( qSTB-3D.1 ), contributed by SHW.035 and detected in response to four of the five isolates, defining a 23.7 Mb candidate resistance-associated interval. This interval encompasses the Stb16q region but also contains other plausible resistance candidates, including a WAK close to the strongest association at 609.21 Mb; the causal basis therefore remains unresolved. Additional isolate-specific resistance-associated intervals were detected on chromosomes 1B, 2D, 3A, and 6D. In a BC ₂ F ₂ population derived from a resistant SHW.035-derived NAM line, pycnidia suppression segregated in a 3:1 ratio consistent with a single dominant factor, whereas necrosis showed more complex inheritance. These findings show that Niab SHWs are a valuable source of STB resistance and highlight the potential to select for reduced pathogen reproduction independently of visible leaf damage.

Background: Root hairs play a key role in plant nutrient and water uptake. Historically, root hair traits have largely been quantified manually. As such, this process has been laborious and low-throughput. However, given their importance for plant health and development, high-throughput quantification of root hair morphology could help underpin rapid advances in the genetic understanding of these traits. With recent increases in the accessibility and availability of artificial intelligence (AI) and machine learning techniques, the development of tools to automate plant phenotyping processes has been greatly accelerated. Results: We present pyRootHair, a high-throughput, AI-powered software application to automate root hair trait extraction from microscope images of plant roots grown on agar plates. pyRootHair is capable of batch processing over 600 images per hour without manual input from the end user. In this study, we deploy pyRootHair on a panel of 24 diverse wheat (Triticum aestivum and Triticum turgidum ssp. durum) cultivars and uncover a large, previously unresolved amount of variation in many root hair traits. We show that the overall root hair profile falls under 2 distinct shape categories and that different root hair traits often correlate with each other. We also demonstrate that pyRootHair can be deployed on a range of plant species, including oat (Avena sativa), rice (Oryza sativa), teff (Eragrostis tef), and tomato (Solanum lycopersicum). Conclusions: The application of pyRootHair enables users to rapidly screen a large number of plant germplasm resources for variation in root hair morphology, supporting high-resolution measurements and high-throughput data analysis. This facilitates downstream investigation of the impacts of root hair genetic control and morphological variation on plant performance. pyRootHair is installable via PyPI (https://pypi.org/project/pyRootHair/) and can be accessed on GitHub at https://github.com/iantsang779/pyRootHair.

Bread wheat ( Triticum aestivum ), a cornerstone of global food security contributing ~ 20% of daily caloric intake, faces increasing vulnerability to rapidly evolving pathogens. This is due in part to a narrowed genetic base following domestication and modern breeding. Wild and ancestral wheat relatives are critical reservoirs of disease resistance genes for breeding new, resilient varieties. This review explores the contributions of primary, secondary, and tertiary genepools of wheat to disease resistance, highlighting loci effective against fungal pathogens that threaten European wheat production. It examines the challenges of alien gene transfer including crossability barriers, hybrid necrosis, and suppressor loci and reviews modern breeding tools such as marker-assisted selection, genomic selection, and genome editing for harnessing exotic germplasm. By synthesising current knowledge, this review highlights the vital contribution of ancestral wheat germplasm in enhancing the resilience and productivity of future wheat crops against increasing biotic stresses.

Understanding how crops recruit bacterial and fungal partners for phosphorus (P) nutrition remains incomplete, particularly regarding temporal shifts between P-cycling bacteria and arbuscular mycorrhizal fungi (AMF). We investigated these dynamics using the wheat root hair mutant short root hair 1 (srh1), which is impaired in root hair elongation and may be more dependent on microbial P acquisition compared to the wildtype. We profiled the P-cycling bacterial microbiome and AMF colonization across development and at booting under P-depleted conditions. Before AMF establishment, the root hair mutant rhizosphere was enriched in bacterial organic P-mineralization genes. After AMF colonization increased in both genotypes, this enrichment disappeared, indicating a temporal shift from bacterial to fungal P acquisition. Growing the root hair mutant in P-depleted conditions to booting, when P uptake is highest in wheat, did not induce the mutant to recruit its bacterial P-cycling microbiome. Instead, AMF arbuscule formation was enriched. Collectively, our results reveal a temporal transition in wheat from bacterial to AMF-mediated P nutrition and highlight the compensatory role of the microbiome in plants lacking root hair elongation.

1 Root hairs play a key role in plant nutrient and water uptake. Historically, root hair traits have been largely quantified manually. As such, this process has been laborious and low-throughput. However, given their importance for plant health and development, high-throughput quantification of root hair morphology could help underpin rapid advances in the genetic understanding of these traits. With recent increases in the accessibility and availability of artificial intelligence (AI) and machine learning techniques, the development of tools to automate plant phenotyping processes has been greatly accelerated. Here, we present pyRootHair, a high-throughput, AI-powered software application to automate root hair trait extraction from images of plant roots grown on agar plates. pyRootHair is capable of batch processing over 600 images per hour without manual input from the end user. In this study, we deploy pyRootHair on a panel of 24 diverse wheat cultivars and uncover a large, previously unresolved amount of variation in many root hair traits. We show that the overall root hair profile falls under two distinct shape categories, and that different root hair traits often correlate with each other. We also demonstrate that pyRootHair can be deployed on a range of plant species, including arabidopsis ( Arabidopsis thaliana) , brachypodium ( Brachypodium distachyon ), medicago ( Medicago truncatula ), oat ( Avena sativa ), rice ( Oryza sativa ), teff ( Eragostis tef ) and tomato ( Solanum lycopersicum ). The application of pyRootHair enables users to rapidly screen large numbers of plant germplasm resources for variation in root hair morphology, supporting high-resolution measurements and high-throughput data analysis. This facilitates downstream investigation of the impacts of root hair genetic control and morphological variaton on plant performance.

To meet the demands of a rising human population, plant breeders will need to develop improved crop varieties that maximize yield in the face of increasing pressure on crop production. Historically, the optimization of crop root architecture has represented a challenging breeding target due to the inaccessibility of the root systems. Root hairs, single cell projections from the root epidermis, are perhaps the most overlooked component of root architecture traits. Root hairs play a central role in facilitating water, nutrient uptake, and soil cohesion. Current root hair architectures may be suboptimal under future agricultural production regimes, coupled with an increasingly variable climate. Here, we review the genetic control of root hair development in the world’s three most important crops—rice, maize, and wheat—and highlight conservation of gene function between monocots and the model dicot species Arabidopsis. Advances in genomic techniques including gene editing combined with traditional plant breeding methods have the potential to overcome many inherent issues associated with the design of improved root hair architectures. Ultimately, this will enable detailed characterization of the effects of contrasting root hair morphology strategies on crop yield and resilience, and the development of new varieties better adapted to deliver future food security.

Genome-wide introgression and substitution lines have been developed in many plant species, enhancing mapping precision, gene discovery and the identification and exploitation of variation from wild relatives. Created over multiple generations of crossing and/or backcrossing accompanied by marker-assisted selection, the resulting introgression lines are a fixed genetic resource. In this study we report the development of spring wheat chromosome segment substitution lines generated to systematically capture genetic variation from tetraploid ( Triticum turgidum ssp dicoccoides ) and diploid ( Aegilops tauschii ) progenitor species. Generated in a common genetic background over four generations of backcrossing, the material is a base resource for the mapping and characterisation of wheat progenitor variation. To facilitate further exploitation the final population was genetically characterised using a high- density genotyping array and a range of agronomic and grain traits assessed to demonstrate the the potential use of the populations for trait localisation in wheat.

Climate change will have numerous impacts on crop production worldwide necessitating a broadening of the germplasm base required to source and incorporate novel traits. Major variation exists in crop progenitor species for seasonal adaptation, photosynthetic characteristics, and root system architecture. Wheat is crucial for securing future food and nutrition security and its evolutionary history and progenitor diversity offer opportunities to mine favourable functional variation in the primary gene pool. Here we provide a review of the status of characterisation of wheat progenitor variation and the potential to use this knowledge to inform the use of variation in other cereal crops. Although significant knowledge of progenitor variation has been generated, we make recommendations for further work required to systematically characterise underlying genetics and physiological mechanisms and propose steps for effective use in breeding. This will enable targeted exploitation of useful variation, supported by the growing portfolio of genomics and accelerated breeding approaches. The knowledge and approaches generated are also likely to be useful across wider crop improvement.

Tetraploid landraces of wheat harbour genetic diversity that could be introgressed into modern bread wheat with the aid of marker-assisted selection to address the genetic diversity bottleneck in the breeding genepool. A novel bi-parental Triticum turgidum ssp. dicoccum Schrank mapping population was created from a cross between two landrace accessions differing for multiple physiological traits. The population was phenotyped for traits hypothesised to be proxies for characteristics associated with improved photosynthesis or drought tolerance, including flowering time, awn length, flag leaf length and width, and stomatal and trichome density. The mapping individuals and parents were genotyped with the 35K Wheat Breeders’ single nucleotide polymorphism (SNP) array. A genetic linkage map was constructed from 104 F4 individuals, consisting of 2066 SNPs with a total length of 3295 cM and an average spacing of 1.6 cM. Using the population, 10 quantitative trait loci (QTLs) for five traits were identified in two years of trials. Three consistent QTLs were identified over both trials for awn length, flowering time and flag leaf width, on chromosomes 4A, 7B and 5B, respectively. The awn length and flowering time QTLs correspond with the major loci Hd and Vrn-B3, respectively. The identified marker-trait associations could be developed for marker-assisted selection, to aid the introgression of diversity from a tetraploid source into modern wheat for potential physiological trait improvement.

Wheat grains contain gluten proteins, which harbour immunogenic epitopes that trigger Coeliac disease in 1–2% of the human population. Wheat varieties or accessions containing only safe gluten have not been identified and conventional breeding alone struggles to achieve such a goal, as the epitopes occur in gluten proteins encoded by five multigene families, these genes are partly located in tandem arrays, and bread wheat is allohexaploid. Gluten immunogenicity can be reduced by modification or deletion of epitopes. Mutagenesis technologies, including CRISPR/Cas9, provide a route to obtain bread wheat containing gluten proteins with fewer immunogenic epitopes. In this study, we analysed the genetic diversity of over 600 α- and γ-gliadin gene sequences to design six sgRNA sequences on relatively conserved domains that we identified near coeliac disease epitopes. They were combined in four CRISPR/Cas9 constructs to target the α- or γ-gliadins, or both simultaneously, in the hexaploid bread wheat cultivar Fielder. We compared the results with those obtained with random mutagenesis in cultivar Paragon by γ-irradiation. For this, Acid-PAGE was used to identify T1 grains with altered gliadin protein profiles compared to the wild-type endosperm. We first optimised the interpretation of Acid-PAGE gels using Chinese Spring deletion lines. We then analysed the changes generated in 360 Paragon γ-irradiated lines and in 117 Fielder CRISPR/Cas9 lines. Similar gliadin profile alterations, with missing protein bands, could be observed in grains produced by both methods. The results demonstrate the feasibility and efficacy of using CRISPR/Cas9 to simultaneously edit multiple genes in the large α- and γ-gliadin gene families in polyploid bread wheat. Additional methods, generating genomics and proteomics data, will be necessary to determine the exact nature of the mutations generated with both methods.