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 identifies the AP2/ERF transcription factor GEMMIFER (MpGMFR) as essential for asexual reproduction in the liverwort Marchantia polymorpha, showing that loss of MpGMFR via genome editing or amiRNA abolishes gemma and gemma cup formation, while dexamethasone‑induced activation triggers their development. Transient strong activation of MpGMFR initiates gemma initial cells at the meristem, which mature into functional gemmae, indicating MpGMFR is both necessary and sufficient for meristem‑derived asexual propagule formation.

The study examined leaf pavement cell shape complexity across a natural European aspen (Populus tremula) population, using GWAS to pinpoint the transcription factor MYB305a as a regulator of cell geometry. Functional validation showed that MYB305a expression is induced by drought and contributes to shape simplification, with cell complexity negatively correlated with water-use efficiency and climatic variables of the genotypes' origin.

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.

A genome‑wide association study of 187 bread wheat genotypes identified 812 significant loci linked to 25 spectral vegetation indices under rainfed drought conditions, revealing a major QTL hotspot on chromosome 2A that accounts for up to 20% of variance in greenness and pigment traits. Candidate gene analysis at this hotspot uncovered stress‑responsive genes, demonstrating that vegetation indices are heritable digital phenotypes useful for selection and genetic analysis of drought resilience.

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 investigated the ability of foliar-applied salicylic acid (SA) to alleviate drought stress in the high‑altitude medicinal plant Valeriana wallichii by measuring physiological and biochemical responses during vegetative and flowering stages. SA at specific concentrations improved photosynthetic rates, water‑use efficiency, chlorophyll content, membrane stability, and root biomass under both severe (25% field capacity) and moderate (50% field capacity) drought conditions. These results suggest that SA treatment enhances drought tolerance and productivity in this species.

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 maps the in vivo proximity interactome of Arabidopsis SKP1-LIKE 1 (ASK1) under acute abscisic acid (ABA) signaling and prolonged drought using TurboID-based proximity labeling and quantitative proteomics, revealing condition-specific networks that include both canonical SCF modules and diverse noncanonical partners. Overexpression of ASK1 shifts proteome composition toward drought‑protective and ABA‑responsive proteins while repressing immune and ROS‑scavenging pathways, highlighting ASK1 as a hub that integrates SCF‑dependent and independent pathways to reprogram transcription, translation, and proteostasis during stress adaptation.