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 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 introduces the Botanical Spectrum Analyzer (BSA), a GUI that incorporates a modified U‑Net deep neural network for accurate segmentation of plant images from RGB and hyperspectral (VNIR and SWIR) data. BSA was tested on wheat, barley, and Arabidopsis datasets, achieving >99% accuracy and F1‑scores above 98%, and markedly outperformed commercial tools on root segmentation tasks.
The authors present high‑throughput phenotyping workflows that convert UAV‑derived imagery from various sensors into precise, large‑scale plant trait data, covering canopy temperature, morphology, and spectral indices. They also provide open educational resources—including a website and YouTube channel—with step‑by‑step protocols and example scripts to streamline the entire drone data processing pipeline.
The study shows that the SnRK1 catalytic subunit KIN10 directs tissue-specific growth‑defense programs in Arabidopsis thaliana by reshaping transcriptomes. kin10 knockout mutants exhibit altered root transcription, reduced root growth, and weakened defense against Pseudomonas syringae, whereas KIN10 overexpression activates shoot defense pathways, increasing ROS and salicylic acid signaling at the cost of growth.