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 examined how DNA methylation influences cold stress priming in Arabidopsis thaliana, revealing that primed plants exhibit distinct gene expression and methylation patterns compared to non-primed plants. DNA methylation mutants, especially met1 lacking CG methylation, showed altered cold memory and misregulation of the CBF gene cluster, indicating that methylation ensures transcriptional precision during stress recall.

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 used paired whole‑genome bisulphite sequencing and RNA‑seq on wheat landraces to investigate how DNA methylation patterns change during drought stress, revealing antagonistic trends across cytosine contexts and a key demethylation role for ROS1a family members. Gene‑body methylation correlated positively with expression but negatively with stress‑responsive changes, while drought‑induced hyper‑methylation of specific transposable elements, especially the RLX_famc9 LTR retrotransposon, appears to modulate downstream gene regulation via siRNA precursors.

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 examined DNA methylation dynamics in Arabidopsis thaliana shoots and roots under heat, phosphate deficiency, and combined stress using whole-genome bisulfite sequencing, small RNA‑seq, and RNA‑seq. Distinct stress‑specific methylation patterns were identified, with heat and combined stress causing CHH hypomethylation, phosphate deficiency causing hyper‑ and hypomethylation in shoots and roots respectively, and the combined stress exhibiting a unique signature independent of additive effects. Methylation changes were concentrated in transposable elements and regulatory regions, implicating RdDM and CMT2 pathways and suggesting a role in chromatin accessibility rather than direct transcriptional control.

The study examines how ectopic accumulation of methionine in Arabidopsis thaliana leaves, driven by a deregulated AtCGS transgene under a seed‑specific promoter, reshapes metabolism, gene expression, and DNA methylation. High‑methionine lines exhibit increased amino acids and sugars, activation of stress‑hormone pathways, and reduced expression of DNA methyltransferases, while low‑methionine lines show heightened non‑CG methylation without major transcriptional changes. Integrated transcriptomic and methylomic analyses reveal a feedback loop linking sulfur‑carbon metabolism, stress adaptation, and epigenetic regulation.

The study mapped the cis‑regulatory landscape of the winter rapeseed cultivar Express617, identifying thousands of novel regulatory elements and characterizing super‑enhancers that are asymmetrically enriched in the Cn subgenome of Brassica napus. An in‑silico pipeline combining population‑level expression data and machine‑learning models revealed that many SE‑associated genes are expressed above predicted levels, and structural variants disrupting SEs lead to reduced gene expression, highlighting their functional importance for gene regulation and breeding.

The study investigates the wheat Pm3 NLR allelic series, revealing that near-identical Pm3d and Pm3e alleles confer broad-spectrum resistance by recognizing multiple, structurally diverse powdery mildew effectors. Using chimeric NLR constructs, the authors pinpoint specificity-determining polymorphisms and demonstrate that engineered combinations of Pm3d and Pm3e further expand effector recognition, showcasing the potential for durable wheat protection through NLR engineering.