The study investigates the gene regulatory network (GRN) controlling flowering time in the allotetraploid crop Brassica napus by comparing its transcriptome to that of Arabidopsis thaliana. While most orthologous gene pairs show conserved expression dynamics, several flowering‑time genes display regulatory divergence, especially under cold conditions, indicating subfunctionalisation among paralogues. Despite these differences, the overall GRN topology remains similar to Arabidopsis, likely due to retention of multiple paralogues.

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 shows that maize plants carrying autophagy-defective atg10 mutations exhibit delayed flowering and significant reductions in kernel size, weight, and number, culminating in lower grain yield. Reciprocal crossing experiments reveal that the maternal genotype, rather than the seed genotype, primarily drives the observed kernel defects, suggesting impaired nutrient remobilization from maternal tissues during seed development.

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.

Thermopriming enhances heat stress tolerance by orchestrating protein maintenance pathways: it activates the heat shock response (HSR) via HSFA1 and the unfolded protein response (UPR) while modulating autophagy to clear damaged proteins. Unprimed seedlings cannot mount these responses, leading to proteostasis collapse, protein aggregation, and death, highlighting the primacy of HSR and protein maintenance over clearance mechanisms.

The study cloned the resistance genes Rmo2 and Rwt7 from barley and wheat, revealing them as orthologous tandem kinase proteins (TKPs) with an N‑terminal heavy metal‑associated (HMA) domain. Domain‑swapping experiments indicated that the HMA domain dictates effector specificity, supporting a model of TKP diversification into paralogs and orthologs that recognize distinct pathogen effectors.

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.

Mutations in the plastid division gene PARC6 and the granule initiation gene BGC1 were combined to generate wheat plants with dramatically enlarged A-type starch granules, some exceeding 50 µm, without affecting plant growth, grain size, or overall starch content. The parc6 bgc1 double mutant was evaluated in both glasshouse and field trials, and the giant granules displayed altered viscosity and pasting temperature, offering novel functional properties for food and industrial applications.

The researchers performed a large‑scale field trial with 105 wheat (Triticum aestivum) genotypes inoculated by Fusarium culmorum, combining quantitative deoxynivalenol (DON) profiling and untargeted metabolomics to uncover molecular signatures of infection. Sesquiterpene‑derived metabolites tracked toxin accumulation, whereas glycosylated diterpene conjugates were enriched in low‑DON samples, indicating a potential defensive metabolic pathway.

The study used comparative transcriptomics of dorsal and ventral petals across development, alongside expression profiling in floral symmetry mutants, to identify genes linked to dorsal (AmCYC-dependent) and ventral (AmDIV-dependent) identities in Antirrhinum majus. In situ hybridisation validated axis‑specific and boundary‑localized expression patterns, revealing that a conserved NGATHA‑LIKE1‑BRASSINAZOLE‑RESISTANT1‑miR164 module has been co‑opted to regulate AmDIV targets and shape the corolla. These findings delineate regulatory modules coordinating dorsoventral and proximal‑distal patterning in zygomorphic flowers.