The study identifies the circadian clock component ELF3 as a temporal gatekeeper that limits hormone‑induced pericycle proliferation and lateral root development in Arabidopsis thaliana. Time‑resolved transcriptomics, imaging, and genetic analyses show that ELF3 maintains rhythmic expression of key regulators via LNK1 and MADS‑box genes, and that loss of ELF3 disrupts this rhythm, enhancing callus growth and accelerating root organogenesis.

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 reveals that the microtubule-associated protein MAP70-2 integrates mechanical and biochemical signals to guide division plane orientation during early lateral root primordium formation in Arabidopsis thaliana. Dynamic MAP70-2 localization to cell corners and the cortical division zone precedes cytokinesis, and loss of MAP70-2 results in misoriented divisions and malformed lateral roots, highlighting its role in three‑dimensional differential growth under mechanical constraints.

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 tests whether heavy‑metal stress contributed to maize domestication by exposing teosinte (Zea mays ssp. parviglumis) and the Palomero toluqueno landrace to sublethal copper and cadmium, then analysing genetic diversity, selection signatures, and transcriptomic responses of three chromosome‑5 heavy‑metal response genes (ZmHMA1, ZmHMA7, ZmSKUs5). Results reveal strong positive selection on these genes, heavy‑metal‑induced phenotypes resembling modern maize, and up‑regulation of Tb1, supporting a role for volcanic‑derived metal stress in early maize evolution.

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.

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 study establishes a tractable system using the large bloom-forming diatom Coscinodiscus granii and its natural oomycete parasite Lagenisma coscinodisci, enabling manual isolation of single host cells and stable co-cultures. High‑quality transcriptomes for both partners were assembled, revealing diverse oomycete effectors and a host transcriptional response involving proteases and exosome pathways, while also profiling the co‑occurring heterotrophic flagellate Pteridomonas sp. This tripartite platform provides a unique marine model for dissecting molecular mechanisms of oomycete‑diatom interactions.

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.