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 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 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 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 study integrated metabolomic and transcriptomic analyses of red clover (Trifolium pratense) roots infected with Fusarium oxysporum and Phoma medicaginis to identify candidate cytochrome P450 enzymes responsible for the methylenedioxy bridge formation in (-)-maackiain biosynthesis. Using co‑expression network analysis and phylogenetic screening, five P450 candidates were selected and screened in engineered Saccharomyces cerevisiae, revealing TpPbS/CYP76F319 as the enzyme catalyzing conversion of calycosin to pseudobaptigenin. This discovery enables reconstruction of the complete (-)-maackiain pathway for potential health and agricultural applications.

The study investigated how barley (Hordeum vulgare) adjusts mitochondrial respiration under salinity stress using physiological, biochemical, metabolomic and proteomic approaches. Salt treatment increased respiration and activated the canonical TCA cycle, while the GABA shunt remained largely inactive, contrasting with wheat responses.

The study examined drought tolerance across nine provenances of the conifer Pinus nigra using high‑throughput phenotyping combined with metabolomic and transcriptomic analyses under controlled soil‑drying conditions. Drought tolerance, measured by the decline in Fv/Fm, varied among provenances but was not linked to a climatic gradient and was independent of growth, with tolerant provenances showing distinct flavonoid and diterpene profiles and provenance‑specific gene expression patterns. Integrating phenotypic and molecular data revealed metabolic signatures underlying drought adaptation in this non‑model conifer.

The study systematically identified heterosis-associated genes and metabolites in rice, functionally validated three genes influencing seedling length, and integrated these molecules into network modules to explain heterosis variance. Predominant additive and partially dominant inheritance patterns were linked to parental genomic variants and were shown to affect 17 agronomic traits in rice, as well as yield heterosis in maize and biomass heterosis in Arabidopsis. The work highlights the quantitative contribution of transcriptomic and metabolomic variation, especially in phenylpropanoid biosynthesis, to hybrid vigor.

The study examined five geographically diverse accessions of the hummingbird‑pollinated monkeyflower Mimulus cardinalis, revealing extensive variation in floral morphology, nectar composition, pigment biochemistry, and scent that influence pollinator perception. Integrating metabolomics, morphology, transcriptomics, and whole‑genome sequencing, the authors identified genetic differences underlying the independent evolution of yellow flowers at range edges. These findings highlight how climate, pollinator interactions, and multi‑trait diversification drive early stages of floral divergence.