The study demonstrates that short‑term low phosphate treatment delays leaf senescence in rice by increasing photosynthetic pigments, enhancing antioxidant enzyme activities, and reducing oxidative damage, whereas high phosphate accelerates senescence. CRISPR/Cas9 editing of MIR827 to lower Pi levels also postpones senescence, while overexpression of MIR827 or MIR399, which raises Pi, speeds it up. Transcriptomic profiling reveals coordinated changes in senescence‑associated and metabolic pathways underlying the low‑phosphate response.

Phosphite (Phi) and phosphate (Pi) share the same root uptake system, but Phi acts as a biostimulant that modulates plant growth and disease resistance in a species‑ and Pi‑dependent manner. In Arabidopsis, Phi induces hypersensitive‑like cell death and enhances resistance to Plectosphaerella cucumerina, while in rice it counteracts Pi‑induced susceptibility to Magnaporthe oryzae and Fusarium fujikuroi, accompanied by extensive transcriptional reprogramming.

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 generated a dataset of 420 sgRNAs targeting promoters, exons, and introns of 137 tomato genes in protoplasts, linking editing efficiency to chromatin accessibility, genomic context, and sequence features. Open chromatin sites showed higher editing rates, while transcriptional activity had little effect, and a subset of guides produced near‑complete editing with microhomology‑mediated deletions. Human‑trained prediction models performed poorly, highlighting the need for plant‑specific guide design tools.

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 examined how elevated atmospheric CO₂ (550 ppm) affects immunity in the C₄ cereal maize (Zea mays L.) by exposing plants grown under ambient and elevated CO₂ to a range of pathogens. Elevated CO₂ increased susceptibility to sugarcane mosaic virus, decreased susceptibility to several bacterial and fungal pathogens, and left susceptibility to others unchanged, with reduced bacterial disease linked to heightened basal immune responses. These findings provide a baseline for future investigations into CO₂‑responsive defense mechanisms in C₄ crops.

The study characterizes the plant spliceosomal protein AtSF1 in Arabidopsis thaliana, using iCLIP and RNA‑seq to map its in vivo branch point binding sites and demonstrate that loss of AtSF1 causes widespread 3' splice‑site mis‑selection. Structural comparison reveals a plant‑specific domain architecture, and the identified AtSF1 targets are enriched for circadian and defense genes, linking splicing regulation to timing and immunity.

The study examined how DNA methylation influences cold stress priming in Arabidopsis thaliana, revealing that primed plants exhibit distinct gene expression and methylation patterns compared to non-primed plants. DNA methylation mutants, especially met1 lacking CG methylation, showed altered cold memory and misregulation of the CBF gene cluster, indicating that methylation ensures transcriptional precision during stress recall.