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 authors used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

Four barley genotypes were examined under simultaneous Fusarium culmorum infection and drought, revealing genotype-dependent Fusarium Head Blight severity and largely additive transcriptomic responses dominated by drought. Co‑expression and hormone profiling linked ABA and auxin to stress‑specific gene modules, and a multiple linear regression model accurately predicted combined‑stress gene expression from single‑stress data, suggesting modular regulation.

The study examined nitrogen use strategies in the model alga Chlamydomonas reinhardtii by comparing growth on ammonium, nitrate, and urea, finding similar molar nitrogen utilization efficiency under saturating conditions. Rapid nitrogen uptake and storage were demonstrated through pulse experiments, and source‑specific transcriptome analysis revealed distinct regulation of assimilation pathways and transporters, supporting a model of flexible nitrogen acquisition and storage.

The study investigates how maternal environmental conditions, specifically temperature and light intensity, influence seed longevity in eight Arabidopsis thaliana natural accessions. Seeds developed under higher temperature (27 °C) and high light showed increased longevity, with transcriptome analysis of the Bor-4 accession revealing dynamic changes in stored mRNAs, including upregulation of antioxidant defenses and raffinose family oligosaccharides. These findings highlight the genotype‑dependent modulation of seed traits by the maternal environment.

The study presents an optimized Agrobacterium-mediated transformation protocol for bread wheat that incorporates a GRF4‑GIF1 fusion to enhance regeneration and achieve genotype‑independent transformation across multiple cultivars. The approach consistently improves transformation efficiency while limiting pleiotropic effects, offering a versatile platform for functional genomics and gene editing in wheat.

The study investigates the evolutionary shift from archegonial to embryo‑sac reproduction by analyzing transcriptomes of Ginkgo reproductive organs and related species. It reveals that the angiosperm pollen‑tube guidance module MYB98‑CRP‑ECS is active in mature Ginkgo archegonia and that, while egg cell transcription is conserved, changes in the fate of other female gametophyte cells drove the transition, providing a molecular framework for this major reproductive evolution.

A comparative physiological study of persimmon cultivars with flat (Hiratanenashi) and round (Koushimaru) fruit shapes revealed that differences in cell proliferation, cell shape, and size contribute to shape variation. Principal component analysis of elliptic Fourier descriptors tracked shape changes, while histology and transcriptome profiling identified candidate genes, including a WOX13 homeobox gene, potentially governing fruit shape development.

The study investigates the role of the Arabidopsis transcription factor AtMYB93 in sulfur (S) signaling and root development, revealing that AtMYB93 mutants exhibit altered expression of S transport and metabolism genes and increased shoot S levels, while tomato plants overexpressing SlMYB93 show reduced shoot S. Transcriptomic profiling, elemental analysis, and promoter activity assays indicate that AtMYB93 contributes to root responses to S deprivation, though functional redundancy masks clear phenotypic effects on lateral and adventitious root formation.