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.

The study used phylogeny‑based analyses of 36 legume genomes and a newly created multiparent advanced generation intercross (MAGIC) population of common bean to predict and characterize genome‑wide deleterious mutations. Machine‑learning integration of conservation and protein features identified thousands of potentially deleterious sites, whose variation correlated negatively with flowering time, maturity, and yield, highlighting the impact of genetic load on breeding performance.

The authors introduce S²-PepAnalyst, a web-based tool that leverages plant-specific datasets and advanced machine learning to predict small signaling peptides (SSPs) with 99.5% accuracy and minimal false negatives. By integrating protein language models, geometric‑topological analysis, and reinforcement learning, the tool surpasses existing predictors such as SignalP 6.0 in classifying peptide families like CLE and RALF.

Populus VariantDB v3.2 is a searchable database that catalogs sequence polymorphisms across heterozygous poplar genomes, enabling precise design of guide RNAs and primers for CRISPR genome editing in outcrossing tree species. The tool accepts short sequence inputs, supports multiple Populus genomes (including hybrids), and provides customizable search parameters to improve gRNA/primer design accuracy. Its platform‑agnostic and expandable architecture makes it broadly applicable to sequence‑sensitive functional genomics studies.

The study used comparative transcriptomics across Erysimum species to identify two 2‑oxoglutarate‑dependent dioxygenases, CARD5 and CARD6, responsible for the 14β‑ and 21‑hydroxylation steps in cardenolide biosynthesis in Erysimum cheiranthoides. Knockout mutants lacking these genes accumulated pathway intermediates, and transient expression in Nicotiana benthamiana confirmed their enzymatic functions, while structural modeling pinpointed residues linked to neofunctionalization.

The study used comparative and de‑novo transcriptomic analyses in poplar to uncover plant and fungal gene regulons that govern ectomycorrhizal (ECM) compatibility, distinguishing general fungal‑sensing responses from ECM‑specific pathways. Key findings include modulation of jasmonic acid‑related defenses, coordinated regulation of secretory and cell‑wall remodeling genes, and dynamic expression of the Common Symbiosis Pathway during early and mature symbiosis stages.

The study compared early protective, repair, and stress responses to chronic gamma irradiation in the radiosensitive conifer Norway spruce (Picea abies) and the radiotolerant Arabidopsis thaliana. Norway spruce exhibited growth inhibition, mitochondrial damage, and higher DNA damage at low dose rates, while Arabidopsis maintained growth, showed minimal organelle damage, and activated DNA repair and antioxidant genes even at the lowest dose rates. Transcriptomic analysis revealed that the tolerant species mounts a robust transcriptional response at low doses, whereas the sensitive species only responds at much higher doses.

The study evaluated 11 intermediate phenotypes linked to stalk lodging resistance in a diverse panel of 566 maize (Zea mays L.) inbred lines across four environments, preserving individual stalk identity to capture plant-level variation. This high-density phenotypic dataset enabled statistical genomics, predictive modeling, and machine learning to uncover genetic factors underlying lodging resistance, offering insights applicable to other grass species.

The study used comparative transcriptomics to examine how Fusarium oxysporum isolates with different lifestyles on angiosperms regulate effector genes during infection of the non‑vascular liverwort Marchantia polymorpha. Core effector genes on fast core chromosomes are actively expressed in the bryophyte host, while lineage‑specific effectors linked to angiosperm pathogenicity are silent, and disruption of a compatibility‑associated core effector alters the expression of other core effectors, highlighting conserved fungal gene networks across plant lineages.

The study utilizes explainable artificial intelligence (XAI) combined with machine learning to assess how inter‑annual weather variability influences oilseed sunflower yields across the United States from 1976 to 2022. Key climate predictors, especially summer maximum temperature and total precipitation, were identified, and predictive models were projected under various Shared Socioeconomic Pathways to 2080, revealing region‑specific yield declines.