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 used a bottom‑up thermodynamic modelling framework to investigate how plants decode calcium signals, starting from Ca2+ binding to EF‑hand proteins and extending to higher‑order decoding modules. They identified six universal Ca2+-decoding modules that can explain variations in calcium sensitivity among kinases and provide a theoretical basis for interpreting calcium signal amplitude and frequency in plant cells.

The study applied a novel Stomatal Patterning Phenotype (SPP) spatial analysis to high‑throughput phenotyping data from 180 maize recombinant inbred lines, dissecting stomatal density into component traits related to cell size, packing, and positional probabilities. Using these derived traits, the authors built a structural equation model that explained 74% of stomatal density variation and identified specific quantitative trait loci for lateral and longitudinal stomatal patterning.