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 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 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 compared expression of aldehyde dehydrogenase (ALDH) families in the moss Physcomitrium patens and barley Hordeum vulgare under stress, highlighting distinct patterns especially in the GABA‑shunt‑related ALDH5, ALDH10 and ALDH21 families. Functional analyses—including kinetic assays, crystal structure determination of PpALDH5F1, and knockout mutants—revealed that loss of specific ALDH genes in moss impairs growth, alters GABA, glutamate and glutamine levels, and triggers up‑regulation of glutathione‑S‑transferase genes as a compensatory oxidative‑stress response.

The study identified the poplar homolog of Arabidopsis HDG11 and generated transgenic poplar hybrids overexpressing PtaHDG11. Constitutive expression conferred markedly improved drought tolerance, as evidenced by higher leaf water content, reduced oxidative damage, up‑regulation of antioxidant genes, and greater post‑stress biomass, while also causing a glabrous phenotype. These results highlight PtaHDG11 as a promising target for breeding drought‑resilient trees.

The study establishes Aeschynomene evenia as a new model for dissecting legume immunity against the soilborne pathogen Aphanomyces euteiches and its relationship with Nod factor-independent symbiosis. Quantitative resistance was assessed through inoculation assays, phenotypic and cytological analyses, and RNA‑seq identified thousands of differentially expressed genes, highlighting immune signaling and specialized metabolism, with mutant analysis confirming dual‑function kinases that modulate resistance. Comparative transcriptomics with Medicago truncatula revealed conserved and unique immune responses, positioning the A. evenia–A. euteiches system as a valuable platform for exploring quantitative resistance and symbiosis integration.

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.

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.

The authors performed a genome-wide analysis of 53 CCCH zinc‑finger genes in pearl millet, identified seven stress‑responsive members and demonstrated that overexpressing PgC3H50 in Arabidopsis enhances drought and salt tolerance. They showed that the ABA‑responsive transcription factor PgAREB1 directly binds the PgC3H50 promoter, activating its expression, as confirmed by yeast one‑hybrid, dual‑luciferase and EMSA assays, defining a new PgAREB1‑PgC3H50 regulatory module.