Genetius

The study generated the first single‑nucleus RNA‑sequencing dataset of tomato (Solanum lycopersicum) roots colonized by the arbuscular mycorrhizal fungus Rhizophagus irregularis, revealing distinct transcriptional programs in epidermal and cortical cells across stages of arbuscule development. Using unsupervised subclustering and a Motif‑Informed Network Inference (MINI‑EX) approach, the authors identified candidate transcription factors that may coordinate cell‑cycle reactivation and nutrient integration during symbiosis, offering a resource for future functional genetics.

The study assessed three savory essential oil–based formulations for controlling early blight caused by Alternaria solani in tomato, finding that formulation CC2020 most effectively reduced disease severity in both in vitro and greenhouse trials. CC2020 also helped maintain tomato fruit vitamin C levels and lowered fungal melanin production, indicating dual benefits for disease suppression and fruit quality.

Using diverse Mexican maize varieties and a MAGIC population, the study demonstrated that leaf vein density is both variable and plastic, correlating positively with photosynthetic rates for small intermediate veins and increasing under heat in drought-adapted lines. Twelve QTLs linked to vein patterning were identified, highlighting candidate genes for intermediate vein development and shedding light on the evolution of high-efficiency C4 leaf architecture.

The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

The study assessed 17 morphological, biochemical, and salt‑stress tolerance traits in 19 maize (Zea mays) landrace accessions from northern Argentina, revealing substantial variation both within and among accessions. Redundancy analysis linked phenotypic variation to the altitude of the collection sites, underscoring the potential of these landraces as sources of diverse biochemical and stress‑related traits for breeding.

The study tests whether heavy‑metal stress contributed to maize domestication by exposing teosinte (Zea mays ssp. parviglumis) and the Palomero toluqueno landrace to sublethal copper and cadmium, then analysing genetic diversity, selection signatures, and transcriptomic responses of three chromosome‑5 heavy‑metal response genes (ZmHMA1, ZmHMA7, ZmSKUs5). Results reveal strong positive selection on these genes, heavy‑metal‑induced phenotypes resembling modern maize, and up‑regulation of Tb1, supporting a role for volcanic‑derived metal stress in early maize evolution.

The study cloned the resistance genes Rmo2 and Rwt7 from barley and wheat, revealing them as orthologous tandem kinase proteins (TKPs) with an N‑terminal heavy metal‑associated (HMA) domain. Domain‑swapping experiments indicated that the HMA domain dictates effector specificity, supporting a model of TKP diversification into paralogs and orthologs that recognize distinct pathogen effectors.

Mutations in the plastid division gene PARC6 and the granule initiation gene BGC1 were combined to generate wheat plants with dramatically enlarged A-type starch granules, some exceeding 50 µm, without affecting plant growth, grain size, or overall starch content. The parc6 bgc1 double mutant was evaluated in both glasshouse and field trials, and the giant granules displayed altered viscosity and pasting temperature, offering novel functional properties for food and industrial applications.

The researchers performed a large‑scale field trial with 105 wheat (Triticum aestivum) genotypes inoculated by Fusarium culmorum, combining quantitative deoxynivalenol (DON) profiling and untargeted metabolomics to uncover molecular signatures of infection. Sesquiterpene‑derived metabolites tracked toxin accumulation, whereas glycosylated diterpene conjugates were enriched in low‑DON samples, indicating a potential defensive metabolic pathway.

The study demonstrates that subfamily I ethylene receptors form the core ethylene‑sensing module and act epistatically over subfamily II receptors, uniquely possessing Ca2+‑permeable channel activity that drives ethylene‑induced cytosolic calcium influx. This reveals a mechanistic link whereby subfamily I receptors integrate hormone perception with calcium signaling in plants.