The study used transcriptomic profiling to compare tomato (Solanum lycopersicum) responses to three evolutionarily distant pathogens—nematodes, aphids, and oomycetes—during compatible interactions, identifying differentially expressed genes and key host hubs. Integrating public datasets and performing co‑expression and GO enrichment analyses, the authors mapped shared dysregulation clusters and employed Arabidopsis interactome data to place tomato candidates within broader networks, highlighting potential targets for multi‑pathogen resistance.

The study demonstrates that plasmodesmata‑located protein 5 (PDLP5) interacts with plasma membrane intrinsic proteins (PIPs) to inhibit H2O2 transport across the plasma membrane in Arabidopsis. Overexpression of PDLP5 reduces H2O2 uptake and diminishes H2O2‑induced root growth inhibition, whereas pdlp5 mutants show enhanced sensitivity, with PIP2;5 identified as a key target of this regulation.

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 used live-cell fluorescence imaging of Arabidopsis thaliana pollen tubes co-expressing labeled tubulin and actin to reveal partial co-localization of the two cytoskeletal networks. Pharmacological disruption showed that microtubules depend on actin for stability in the medial region, while actin remains unaffected by microtubule loss, indicating spatially dependent cytoskeletal crosstalk. Tracking of the microtubule plus‑end binding protein EB1b demonstrated that the microtubule array is primarily parallel with plus ends oriented away from the apex.

The study demonstrates that invasion of Arabidopsis thaliana roots by the parasitic plant Phtheirospermum japonicum induces a phosphate‑starvation response in the host, which in turn leads to systemic suppression of immunity. This immunosuppression makes Arabidopsis more vulnerable to secondary microbial infections, highlighting the importance of multitrophic interactions in crop resilience.

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 identifies the circadian clock component ELF3 as a temporal gatekeeper that limits hormone‑induced pericycle proliferation and lateral root development in Arabidopsis thaliana. Time‑resolved transcriptomics, imaging, and genetic analyses show that ELF3 maintains rhythmic expression of key regulators via LNK1 and MADS‑box genes, and that loss of ELF3 disrupts this rhythm, enhancing callus growth and accelerating root organogenesis.

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.