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 generated a dataset of 420 sgRNAs targeting promoters, exons, and introns of 137 tomato genes in protoplasts, linking editing efficiency to chromatin accessibility, genomic context, and sequence features. Open chromatin sites showed higher editing rates, while transcriptional activity had little effect, and a subset of guides produced near‑complete editing with microhomology‑mediated deletions. Human‑trained prediction models performed poorly, highlighting the need for plant‑specific guide design tools.

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 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.

The study integrates genome, transcriptome, and chromatin accessibility data from 380 soybean accessions to dissect the genetic and regulatory basis of symbiotic nitrogen fixation (SNF). Using GWAS, TWAS, eQTL mapping, and ATAC-seq, the authors identify key loci, co‑expression modules, and regulatory elements, and validate the circadian clock gene GmLHY1b as a negative regulator of nodulation via CRISPR and CUT&Tag. These resources illuminate SNF networks and provide a foundation for soybean improvement.

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.

The study constructs a ~1‑million‑cell single‑nuclei transcriptome atlas of Arabidopsis leaves to reveal that drought stress accelerates transcriptional programs associated with maturation and aging, thereby limiting leaf growth in proportion to stress intensity. Targeted upregulation of FERRIC REDUCTION OXIDASE 6 in mesophyll cells partially rescues leaf growth under drought, demonstrating the functional relevance of these transcriptional changes.