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.

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 created a system that blocks root‑mediated signaling between wheat varieties in a varietal mixture and used transcriptomic and metabolomic profiling to reveal that root chemical interactions drive reduced susceptibility to Septoria tritici blotch, with phenolic compounds emerging as key mediators. Disruption of these root signals eliminates both the disease resistance phenotype and the associated molecular reprogramming.

The study characterizes the chloroplast‑localized protein AT4G33780 in Arabidopsis thaliana using CRISPR/Cas9 knockout and overexpression lines, revealing tissue‑specific expression and context‑dependent effects on seed germination, seedling growth, vegetative development, and root responses to nickel stress. Integrated transcriptomic (RNA‑seq) and untargeted metabolomic analyses show extensive transcriptional reprogramming—especially of cell‑wall genes—and altered central energy metabolism, indicating AT4G33780 coordinates metabolic state with developmental regulation rather than controlling single pathways.

The study shows that maize plants carrying autophagy-defective atg10 mutations exhibit delayed flowering and significant reductions in kernel size, weight, and number, culminating in lower grain yield. Reciprocal crossing experiments reveal that the maternal genotype, rather than the seed genotype, primarily drives the observed kernel defects, suggesting impaired nutrient remobilization from maternal tissues during seed development.

Using the bryophyte Physcomitrium patens, the study shows that loss of autophagy enhances auxin‑driven caulonemata differentiation and colony expansion under low nitrogen or imbalanced carbon/nitrogen conditions, accompanied by higher internal IAA, reduced PpPINA expression, and up‑regulated RSL transcription factors. Autophagy appears to suppress auxin‑induced differentiation during nutrient stress, acting as a hub that balances metabolic cues with hormonal signaling.

Thermopriming enhances heat stress tolerance by orchestrating protein maintenance pathways: it activates the heat shock response (HSR) via HSFA1 and the unfolded protein response (UPR) while modulating autophagy to clear damaged proteins. Unprimed seedlings cannot mount these responses, leading to proteostasis collapse, protein aggregation, and death, highlighting the primacy of HSR and protein maintenance over clearance mechanisms.

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.