The study used transcriptomic profiling to compare tomato (Solanum lycopersicum) responses to three evolutionarily distant pathogens—nematodes, aphids, and oomycetes—during compatible interactions, identifying differentially expressed genes and key host hubs. Integrating public datasets and performing co‑expression and GO enrichment analyses, the authors mapped shared dysregulation clusters and employed Arabidopsis interactome data to place tomato candidates within broader networks, highlighting potential targets for multi‑pathogen resistance.

The authors applied semi‑supervised deep‑learning to super‑resolution images of modern and fossil grass pollen, training convolutional neural networks to extract abstract morphological features. These features were used to quantify past grass community diversity and C3:C4 ratios in a 25,000‑year lake‑sediment record, revealing a marked diversity loss during the last glacial and a gradual decline of C4 grasses in the Holocene.

The authors introduce AdaPoinTr, a geometry-aware transformer that predicts the alpha‑shape of coniferous tree crowns from incomplete terrestrial or mobile laser‑scanning point clouds, focusing on crown reconstruction rather than full tree completion. Trained on synthetically generated partial crowns, the model consistently improves crown shape similarity and reduces height estimation bias across three diverse forest datasets, providing a cost‑effective solution for enhanced 3D forest structural monitoring.

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 establishes Aeschynomene evenia as a new model for dissecting legume immunity against the soilborne pathogen Aphanomyces euteiches and its relationship with Nod factor-independent symbiosis. Quantitative resistance was assessed through inoculation assays, phenotypic and cytological analyses, and RNA‑seq identified thousands of differentially expressed genes, highlighting immune signaling and specialized metabolism, with mutant analysis confirming dual‑function kinases that modulate resistance. Comparative transcriptomics with Medicago truncatula revealed conserved and unique immune responses, positioning the A. evenia–A. euteiches system as a valuable platform for exploring quantitative resistance and symbiosis integration.

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 characterizes a radiation‑induced root‑suppressed (Rs) mutant in tomato that displays dwarfism and pleiotropic defects in leaves, flowers, and fruits. Metabolite profiling and rescue with H2S donors implicate disrupted sulfur metabolism, and whole‑genome sequencing identifies promoter mutations in two root‑meristem‑specific sulfotransferase genes as likely contributors to the root phenotype.

The study identifies members of the REMORIN protein family as inhibitors of plasma membrane H⁺‑ATPases, leading to extracellular pH alkalinization that modulates cell surface processes such as steroid hormone signaling and coordinates root developmental transitions in Arabidopsis thaliana. This inhibition represents an ancient mechanism predating root evolution, suggesting that extracellular pH patterning has shaped plant morphogenesis.

The study examined how dual‑purpose hemp (Cannabis sativa) adjusts to different phosphate levels, showing that flower biomass is maintained unless phosphate is completely removed. Integrated physiological measurements and transcriptomic profiling revealed that phosphate is reallocated to flowers via glycolytic bypasses and organic phosphate release, while key regulatory genes followed expected patterns but did not suppress uptake at high phosphate, leading to nitrate depletion that limits growth.

Using ten Phaeodactylum tricornutum mutant strains with graded constitutive Lhcx1 expression, the study links NPQ induction under high light to physiological outcomes (oxidized QA, increased cyclic electron flow) and extensive transcriptomic reprogramming, affecting nearly half the genome. The approach demonstrates that higher NPQ mitigates PSII damage, boosts ATP production for repair, and drives distinct gene regulatory networks, providing a model framework for dissecting photosynthetic and gene expression integration.