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 reveals that each individual plant possesses a statistically unique leaf appearance that can be discriminated using convolutional neural network (CNN) based deep learning, enabling a "plant face" recognition concept. Applications demonstrated include distinguishing leaves from the same species/cultivar, analyzing leaflet positional patterns on compound leaves, assessing bilateral symmetry, and detecting morphological differences linked to stem chirality, highlighting the encoding of genetic, environmental, and developmental information in leaf morphology.

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.

Foliar application of Trichoderma harzianum cell‑free culture filtrates (CF) increased fruit yield, root growth, and photosynthesis in a commercial tomato cultivar under prolonged water deficit in a Mediterranean greenhouse. Integrated physiological, metabolite, and transcriptomic analyses revealed that CF mitigated drought‑induced changes, suppressing about half of water‑stress responsive genes, thereby reducing the plant’s transcriptional sensitivity to water scarcity.

The study used Arabidopsis thaliana mutants with low (vtc2, vtc4) and high (vtc2/OE-VTC2) ascorbate levels to examine how ascorbate concentration affects gene expression and cellular homeostasis. Transcriptomic analysis revealed that altered ascorbate levels modulate defense and stress pathways, and that TAA1/TAR2‑mediated auxin biosynthesis is required for coping with elevated ascorbate in a light‑dependent manner.

The study examined transcriptomic responses of the tropical seagrass Halophila stipulacea from a pristine and an impacted site under single and combined thermal and excess nutrient stress in mesocosms. Combined stress caused greater gene reprogramming than individual stresses, with thermal effects dominating and the impacted population showing reduced plasticity but higher resilience. Core stress‑response genes were identified as potential early field indicators of environmental stress.