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 evaluated whether integrating genomic, transcriptomic, and drone-derived phenomic data improves prediction of 129 maize traits across nine environments, using both linear (rrBLUP) and nonlinear (SVR) models. Multi-omics models consistently outperformed single-omics models, with transcriptomic data especially enhancing cross‑environment predictions and capturing genotype‑by‑environment interactions. The results highlight the added value of combining transcriptomics and phenomics with genotypes for more accurate and generalizable trait prediction in maize.

The study identifies an autophagy pathway that degrades plasma membrane-derived clathrin-coated vesicles (CCVs) during hyperosmotic stress, helping maintain membrane tension as cell volume decreases. Using live imaging and correlative microscopy, the authors show that the TPLATE complex subunits AtEH1/Pan1 and AtEH2/Pan1 act as selective autophagy receptors by directly binding ATG8, thereby removing excess membrane under drought or salt conditions.

Using a controlled field experiment on clonal 35‑year‑old Norway spruce trees, the study examined molecular defense responses to Ips typographus attacks. A multi‑omics approach revealed rapid local increases in jasmonic acid and other phytohormones, leading to differential expression of up to 1,900 genes and corresponding proteomic and metabolomic changes that elevated deterrent compounds such as phenolic aglycones, diterpene resin acids, terpenes, and lignin.

Using integrated metabolomics, fluxomics, and proteomics, the study shows that Bamboo mosaic virus infection in Nicotiana benthamiana redirects carbon flux toward glycolysis and the TCA cycle, enhancing mitochondrial metabolism. Silencing the mitochondrial NAD⁺-dependent malic enzyme 1 disrupts cytoplasmic NADH/NAD⁺ balance and alters defense gene expression, indicating that mitochondrial redox regulation is crucial for antiviral defense.

The study uses a high‑throughput comparative multi‑omics strategy to profile transcript, metabolite, and protein dynamics in Arabidopsis thaliana seedlings throughout the heat‑stress memory (HSM) phase following acquired thermotolerance. Early recovery stages show rapid transcriptional activation of memory‑related genes, while protein levels stay elevated longer, and distinct metabolite patterns emerge, highlighting temporal layers of the memory process.

The study employed a multi‑omics workflow (transcriptomics, ribosome profiling, and proteomics) to uncover small peptides encoded by long non‑coding RNAs (LSEPs) in rice, finding that over 40% of surveyed lncRNAs associate with ribosomes. An optimized small‑peptide extraction followed by LC‑MS/MS identified 403 LSEPs, confirming the peptide‑coding capacity of plant lncRNAs and providing a scalable pipeline for large‑scale screening.