The study examined soybean (Glycine max) responses to simultaneous drought and Asian soybean rust infection using combined transcriptomic and metabolomic analyses. Weighted Gene Co-expression Network Analysis identified stress-specific gene modules linked to metabolites, while Copula Graphical Models uncovered sparse, condition‑specific networks, revealing distinct molecular signatures for each stress without overlapping genes or metabolites. The integrative approach underscores a hierarchical, modular defense architecture and suggests targets for breeding multi‑stress resilient soybeans.

The study identifies the pseudokinase CRN in Medicago truncatula as a regulator of inflorescence meristem branching and a negative modulator of root interactions with arbuscular mycorrhizal (AM) fungi, operating partially independently of the AM autoregulation CLE peptide MtCLE53. Transcriptomic profiling of crn mutant roots reveals disruptions in nutrient, symbiosis, and stress signaling pathways, highlighting the multifaceted role of MtCRN in plant development and environmental interactions.

The study examined how varying temperature regimes, including cold deprivation and early cold exposure, affect dormancy onset and maintenance in sweet cherry (Prunus avium) flower buds. Phenological monitoring combined with transcriptomic analyses revealed that temperature drives dormancy progression, identifying specific genes and pathways responsive to cold, and uncovering a distinct shallow dormancy phase induced by cold deprivation with a unique molecular signature.

The study combined cell biology, transcriptomics, and ionomics to reveal that zinc deficiency reduces root apical meristem size while preserving meristematic activity and local Zn levels, leading to enhanced cell elongation and differentiation in Arabidopsis thaliana. ZIP12 was identified as a highly induced gene in the zinc‑deficient root tip, and zip12 mutants displayed impaired root growth, altered RAM structure, disrupted Zn‑responsive gene expression, and abnormal metal partitioning, highlighting ZIP12’s role in maintaining Zn homeostasis and meristem function.

The study used extensive gravimetric load‑cell and ambient sensor data collected over seven years from hundreds of greenhouse-grown crops to train machine‑learning models for predicting daily whole‑plant transpiration. Random Forest and XGBoost achieved the highest accuracy (R² up to 0.89), with ambient temperature identified as the dominant driver. These results highlight the promise of ML‑based tools for precise agricultural water management.

The study used high-resolution chemical imaging to map cell-type specific metabolic changes in plant roots inoculated with a nine-strain endophyte consortium under drought, revealing that endophytes differentially alter root metabolomes across spatial domains. Machine learning identified metabolites and exudates predictive of drought and endophyte treatment, and correlation analyses showed dynamic endophyte–metabolite relationships under stress.

The study used transcriptomic and lipidomic profiling to investigate how chia (Salvia hispanica) leaves respond to short‑term (3 h) and prolonged (27 h) heat stress at 38 °C, revealing rapid activation of calcium‑signaling and heat‑shock pathways and reversible changes in triacylglycerol levels. Nearly all heat‑responsive genes returned to baseline expression after 24 h recovery, highlighting robust thermotolerance mechanisms that could inform improvement of other oilseed crops.

A comparative physiological study of persimmon cultivars with flat (Hiratanenashi) and round (Koushimaru) fruit shapes revealed that differences in cell proliferation, cell shape, and size contribute to shape variation. Principal component analysis of elliptic Fourier descriptors tracked shape changes, while histology and transcriptome profiling identified candidate genes, including a WOX13 homeobox gene, potentially governing fruit shape development.

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 introduces ENTRAP-seq, a high‑throughput in‑planta assay that couples protein‑coding libraries with a nuclear magnetic sorting‑based reporter to multiplexively assess transcriptional regulatory activity of thousands of protein variants. Using this platform and machine‑learning analysis, the authors screened 1,495 plant viral proteins, uncovering numerous novel regulatory domains, and applied machine‑guided, semi‑rational design to modify the activity of a plant transcription factor.