Transcriptional responses of Solanum lycopersicum to three distinct parasites reveal host hubs and networks underlying parasitic successes
Authors: Truch, J., Jaouannet, M., Da Rocha, M., Kulhanek-Fontanille, E., Van Ghelder, C., Rancurel, C., Migliore, O., Pere, A., Jaubert, S., Coustau, C., Galiana, E., Favery, B.
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 study demonstrates that plasmodesmata‑located protein 5 (PDLP5) interacts with plasma membrane intrinsic proteins (PIPs) to inhibit H2O2 transport across the plasma membrane in Arabidopsis. Overexpression of PDLP5 reduces H2O2 uptake and diminishes H2O2‑induced root growth inhibition, whereas pdlp5 mutants show enhanced sensitivity, with PIP2;5 identified as a key target of this regulation.
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.
A novel pathosystem between Aeschynomene evenia and Aphanomyces euteiches reveals new immune components in quantitative legume root-rot resistance.
Authors: Baker, M., Martinez, Y., Keller, J., Sarrette, B., Pervent, M., Libourel, C., Le Ru, A., Bonhomme, M., Gough, C., Castel, B., ARRIGHI, J.-F., Jacquet, C.
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 profiled the maize (Zea mays) endosperm transcriptome for the first four days after pollination using laser-capture microdissection, revealing temporal co‑expression modules including a fertilization‑activated subset. Network analyses linked MYB‑related transcription factors to basal endosperm transfer layer (BETL) differentiation and E2F transcription factors, together with TOR‑dependent sugar sensing, to early endosperm proliferation and kernel size variation.
The study reveals that REMORIN protein evolution is primarily driven by diversification of their conserved C-terminal domain, defining four major clades. Structural bioinformatics predicts a common membrane‑binding interface with diverse curvatures and lengths, and suggests that some REMs can form C‑terminal‑mediated oligomers, adding complexity to membrane organization.
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.
Evolution of HMA-integrated tandem kinases accompanied by expansion of target pathogens
Authors: Asuke, S., Tagle, A. G., Hyon, G.-S., Koizumi, S., Murakami, T., Horie, A., Niwamoto, D., Katayama, E., Shibata, M., Takahashi, Y., Islam, M. T., Matsuoka, Y., Yamaji, N., Shimizu, M., Terauchi, R., Hisano, H., Sato, K., Tosa, Y.
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.