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 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 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.

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.

Using a forward genetic screen of 284 Arabidopsis thaliana accessions, the study identified extensive natural variation in root endodermal suberin and pinpointed the previously unknown gene SUBER GENE1 (SBG1) as a key regulator. GWAS and protein interaction analyses revealed that SBG1 controls suberin deposition by binding type‑one protein phosphatases (TOPPs), with disruption of this interaction or TOPP loss‑of‑function altering suberin levels, linking the pathway to ABA signaling.

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.