Phosphite (Phi) and phosphate (Pi) share the same root uptake system, but Phi acts as a biostimulant that modulates plant growth and disease resistance in a species‑ and Pi‑dependent manner. In Arabidopsis, Phi induces hypersensitive‑like cell death and enhances resistance to Plectosphaerella cucumerina, while in rice it counteracts Pi‑induced susceptibility to Magnaporthe oryzae and Fusarium fujikuroi, accompanied by extensive transcriptional reprogramming.

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 presents an optimized Agrobacterium-mediated transformation protocol for bread wheat that incorporates a GRF4‑GIF1 fusion to enhance regeneration and achieve genotype‑independent transformation across multiple cultivars. The approach consistently improves transformation efficiency while limiting pleiotropic effects, offering a versatile platform for functional genomics and gene editing in wheat.

The study examines how the SnRK1 catalytic subunit KIN10 integrates carbon availability with root growth regulation in Arabidopsis thaliana. Loss of KIN10 reduces glucose‑induced inhibition of root elongation and triggers widespread transcriptional reprogramming of metabolic and hormonal pathways, notably affecting auxin and jasmonate signaling under sucrose supplementation. These findings highlight KIN10 as a central hub linking energy status to developmental and environmental cues in roots.

The study combined long‑read whole‑genome assembly, multi‑omics profiling (DNA methylation, mRNA, ribosome‑associated transcripts, tRNA abundance, and protein levels) in two Arabidopsis thaliana accessions to evaluate how genomic information propagates through the Central Dogma. Codon usage in gene sequences emerged as the strongest predictor of both mRNA and protein abundance, while methylation, tRNA levels, and ribosome‑associated transcripts contributed little additional information under stable conditions.

The study performed a comprehensive computational analysis of the Arabidopsis thaliana proteome, classifying 48,359 proteins by melting temperature (Tm) and melting temperature index (TI) and linking thermal stability to amino acid composition, molecular mass, and codon usage. Machine‑learning and evolutionary analyses revealed that higher molecular mass and specific codon pairs correlate with higher Tm, and that gene duplication has driven the evolution of high‑Tm proteins, suggesting a genomic basis for stress resilience.