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 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 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 generated time‑resolved transcriptomes (0, 6, 24 h post‑inoculation) from grapevine genotypes carrying single, double, or triple resistance loci against Plasmopara viticola and a susceptible control. Multilocus genotypes showed baseline transcriptional differences and distinct, non‑additive co‑expression network rewiring, with specific immune‑layer dynamics and rapid induction of transcription factors in the triple‑locus line. These findings reveal that pyramiding resistance loci alters the timing, connectivity, and layer allocation of immune‑related transcriptional programs.

The authors performed a meta‑analysis of ~1,900 public maize RNA‑seq datasets spanning six abiotic stresses, applying batch correction and both traditional set operations and a random‑forest classifier to identify a core set of 744 stress‑responsive genes. These core genes are enriched for transcription factor families and, through co‑expression network analysis, appear to coordinate both universal and stress‑specific transcriptional responses, highlighting conserved yet flexible regulatory strategies in Zea mays.