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 used untargeted metabolomics and QTL mapping in a tomato recombinant inbred line population to characterize root exudate composition and identify genetic loci controlling specific metabolites. It reveals domestication-driven changes in exudate profiles and links metabolic QTLs with previously reported microbial QTLs, suggesting a genetic basis for shaping the root microbiome.

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.

A nested association mapping (NAM) population was created in lentil by crossing the cultivar CDC Redberry with 32 diverse genotypes, producing recombinant inbred lines that were field‑phenotyped for days to emergence, flowering, and maturity. Exome capture sequencing and genome‑wide association studies identified 14 significant loci, including both known and novel candidates, demonstrating the NAM design’s ability to uncover minor‑effect loci for complex traits. This publicly available lentil NAM population provides a high‑resolution resource for trait discovery and pre‑breeding.

The study investigated the molecular basis of quantitative resistance to black spot disease in a Rosa wichurana × Rosa chinensis F1 population, identifying two major QTLs (B3 on LG3 and B5 on LG5). RNA‑seq of inoculated and control leaf samples at 0, 3, and 5 days post‑inoculation revealed extensive transcriptional reprogramming, with QTL B3 triggering classic defense pathways and QTL B5 showing a limited, distinct response. These findings highlight complex, QTL‑specific regulation underlying durable black‑spot resistance in roses.

The study applied a novel Stomatal Patterning Phenotype (SPP) spatial analysis to high‑throughput phenotyping data from 180 maize recombinant inbred lines, dissecting stomatal density into component traits related to cell size, packing, and positional probabilities. Using these derived traits, the authors built a structural equation model that explained 74% of stomatal density variation and identified specific quantitative trait loci for lateral and longitudinal stomatal patterning.

The study links circadian rhythm traits in Arabidopsis seedlings to flowering time synchronization across latitudes by mapping QTLs in recombinant inbred lines derived from African and European lineages. Two QTLs containing KH-domain RNA‑binding proteins (KH17, KH29) affect splicing of key flowering regulators (MAF2, MAF3), creating chimeric transcripts that may accelerate proteome evolution and decouple mean flowering time from its synchronization, offering a predictive tool for breeding climate‑resilient crops.