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 authors compiled and standardized published data on Rubisco dark inhibition for 157 flowering plant species, categorizing them into four inhibition levels and analyzing phylogenetic trends. Their meta‑analysis reveals a complex, uneven distribution of inhibition across taxa, suggesting underlying chloroplast microenvironment drivers and providing a new resource for future photosynthesis improvement efforts.

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 genotyped 1,013 hard red spring wheat lines using SNP arrays and targeted KASP markers to track changes in genetic diversity and the distribution of dwarfing Rht alleles over a century of North American breeding. It found shifts from Rht‑D1b to Rht‑B1b dominance, identified low‑frequency dwarf alleles at Rht24 and Rht25 that have increased recently, and revealed gene interactions that can fine‑tune plant height, along with evidence of recent selection for photoperiod sensitivity.

The study performed comparative gene expression profiling across four rice accessions—from shoot apical meristem to primordia stage P5—to delineate developmental and photosynthetic transitions in leaf development. By integrating differential expression and gene regulatory network analyses, the authors identified stage-specific regulatory events and key transcription factors, such as RDD1, ARID2, and ERF3, especially in the wild rice Oryza australiensis, offering a comprehensive framework for optimizing leaf function.

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.

The study functionally characterizes three tomato CNR/FWL proteins (SlFWL2, SlFWL4, SlFWL5) and demonstrates that SlFWL5 localizes to plasmodesmata, where it regulates leaf size and morphology by promoting cell expansion likely through cell‑to‑cell communication. Gain‑ and loss‑of‑function transgenic tomato lines reveal that SlFWL5 is a key regulator of organ growth via modulation of plasmodesmatal signaling.