The study characterizes a conserved RNA structural element named DEAD within DEAD-box helicase genes in land plants, showing that it functions as a sensor of helicase activity to regulate alternative splicing in Arabidopsis thaliana. By modulating the folding of DEAD, the plant balances helicase transcript and protein levels via a negative feedback loop, and loss of this regulation leads to widespread splicing disruptions and severe stress phenotypes.

The study demonstrates that short‑term low phosphate treatment delays leaf senescence in rice by increasing photosynthetic pigments, enhancing antioxidant enzyme activities, and reducing oxidative damage, whereas high phosphate accelerates senescence. CRISPR/Cas9 editing of MIR827 to lower Pi levels also postpones senescence, while overexpression of MIR827 or MIR399, which raises Pi, speeds it up. Transcriptomic profiling reveals coordinated changes in senescence‑associated and metabolic pathways underlying the low‑phosphate response.

Field experiments combined with RNA sequencing revealed that wheat ploidy influences heat stress resilience, with tetraploid T. turgidum showing the smallest yield loss and hexaploid T. aestivum mounting the largest transcriptional response. Ploidy-dependent differences were observed in differential gene expression, alternative splicing—including hexaploid-specific exon skipping of NF‑YB—and co‑expression networks linked to grain traits, highlighting candidate pathways for breeding heat‑tolerant wheat.

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 the first tissue‑specific full‑length transcriptome atlas for Panax vietnamensis var. fuscidiscus using combined PacBio SMRT and Illumina RNA‑Seq, uncovering 281,468 transcripts and 8,089 novel genes. Twenty‑one candidate genes in triterpenoid saponin biosynthesis were identified, along with extensive alternative splicing events that appear to modulate tissue‑specific production of ocotillol‑type ginsenosides.

Using diverse Mexican maize varieties and a MAGIC population, the study demonstrated that leaf vein density is both variable and plastic, correlating positively with photosynthetic rates for small intermediate veins and increasing under heat in drought-adapted lines. Twelve QTLs linked to vein patterning were identified, highlighting candidate genes for intermediate vein development and shedding light on the evolution of high-efficiency C4 leaf architecture.

The study introduces a hybrid modeling framework that integrates a logistic ordinary differential equation with a Long Short-Term Memory neural network to form a Physics-Informed Neural Network (PINN) for predicting wheat plant height. Using only time and temperature as inputs, the PINN outperformed other longitudinal growth models, achieving the lowest average RMSE and reduced variability across multiple random initializations. The results suggest that embedding biological growth constraints within data‑driven models can substantially improve prediction accuracy for plant traits.

The study created a system that blocks root‑mediated signaling between wheat varieties in a varietal mixture and used transcriptomic and metabolomic profiling to reveal that root chemical interactions drive reduced susceptibility to Septoria tritici blotch, with phenolic compounds emerging as key mediators. Disruption of these root signals eliminates both the disease resistance phenotype and the associated molecular reprogramming.

The study establishes Aeschynomene evenia as a new model for dissecting legume immunity against the soilborne pathogen Aphanomyces euteiches and its relationship with Nod factor-independent symbiosis. Quantitative resistance was assessed through inoculation assays, phenotypic and cytological analyses, and RNA‑seq identified thousands of differentially expressed genes, highlighting immune signaling and specialized metabolism, with mutant analysis confirming dual‑function kinases that modulate resistance. Comparative transcriptomics with Medicago truncatula revealed conserved and unique immune responses, positioning the A. evenia–A. euteiches system as a valuable platform for exploring quantitative resistance and symbiosis integration.

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.