Field experiments combined with RNA sequencing revealed that wheat ploidy influences heat stress resilience, with tetraploid T. turgidum showing the smallest yield loss and hexaploid T. aestivum mounting the largest transcriptional response. Ploidy-dependent differences were observed in differential gene expression, alternative splicing—including hexaploid-specific exon skipping of NF‑YB—and co‑expression networks linked to grain traits, highlighting candidate pathways for breeding heat‑tolerant wheat.

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 employed ultra large‑scale 2D clinostats to grow tomato (Solanum lycopersicum) plants beyond the seedling stage under simulated microgravity and upright control conditions across five sequential trials. Simulated microgravity consistently affected plant growth, but the magnitude and direction of the response varied among trials, with temperature identified as a significant co‑variant; moderate heat stress surprisingly enhanced growth under simulated microgravity. These results highlight the utility of large‑scale clinostats for dissecting interactions between environmental factors and simulated microgravity in plant development.

The study demonstrates that the interaction between spliceosomal proteins STA1 and DOT2 controls nuclear speckle organization, pre‑mRNA splicing efficiency, and heat‑stress tolerance in Arabidopsis thaliana. A missense mutation in DOT2 restores the weakened STA1‑DOT2 interaction in the sta1‑1 mutant, linking interaction strength to speckle formation and transcriptome‑wide intron retention under heat stress, while pharmacological inhibition of STA1‑associated speckles reproduces the mutant phenotypes. These findings reveal a heat‑sensitive interaction node that couples spliceosome assembly to nuclear speckle dynamics and splicing robustness.

The study identifies the extended NT‑C2 domain of Plastid Movement Impaired 1 (PMI1) as the main membrane‑binding module that interacts with PI4P and PI(4,5)P2, requiring basic residues for plasma‑membrane association. Calcium binding by the NT‑C2 domain modulates its phosphoinositide preference, and cytosolic Ca2+ depletion blocks blue‑light‑induced PMI1 redistribution, indicating that both the NT‑C2 domain and adjacent intrinsically disordered regions are essential for PMI1’s role in chloroplast movement.

The study identified a heat‑responsive exon‑skipping event in the basic Helix‑Loop‑Helix domain of the transcription factor PIF4, which reduces PIF4 activity and promotes photomorphogenic traits in etiolated seedlings. This reveals a novel post‑transcriptional mechanism by which plants modulate PIF4 function during heat stress.

The study evaluated how stomatal anatomy and physiological efficiency influence wheat heat tolerance across multi‑environment field trials with 200 genotypes, using early versus delayed sowing to impose temperature stress. Findings revealed a decoupling between anatomical capacity (gsmax) and actual conductance (gs, gse) under heat, plastic shifts toward smaller, denser stomata, and identified 125 QTL linked to stomatal traits, suggesting targets for breeding climate‑resilient wheat.

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.

The study identified a critical two‑week window of elevated maternal temperature during weeks 4–5 after flowering that delays dormancy release in weedy rice seeds. Controlled‑environment and field transplant experiments showed that this late‑reproductive‑stage heat exposure postpones germination after after‑ripening, providing insight for predicting seed behavior and improving weed management strategies.