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 examined leaf pavement cell shape complexity across a natural European aspen (Populus tremula) population, using GWAS to pinpoint the transcription factor MYB305a as a regulator of cell geometry. Functional validation showed that MYB305a expression is induced by drought and contributes to shape simplification, with cell complexity negatively correlated with water-use efficiency and climatic variables of the genotypes' origin.
The genetic architecture of leaf vein density traits and its importance for photosynthesis in maize
Authors: Coyac-Rodriguez, J. L., Perez-Limon, S., Hernandez-Jaimes, E., Hernandez-Coronado, M., Camo-Escobar, D., Alonso-Nieves, A. L., Ortega-Estrada, M. d. J., Gomez-Capetillo, N., Sawers, R. J., Ortiz-Ramirez, C. H.
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.
A genome‑wide association study of 187 bread wheat genotypes identified 812 significant loci linked to 25 spectral vegetation indices under rainfed drought conditions, revealing a major QTL hotspot on chromosome 2A that accounts for up to 20% of variance in greenness and pigment traits. Candidate gene analysis at this hotspot uncovered stress‑responsive genes, demonstrating that vegetation indices are heritable digital phenotypes useful for selection and genetic analysis of drought resilience.
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 assessed 17 morphological, biochemical, and salt‑stress tolerance traits in 19 maize (Zea mays) landrace accessions from northern Argentina, revealing substantial variation both within and among accessions. Redundancy analysis linked phenotypic variation to the altitude of the collection sites, underscoring the potential of these landraces as sources of diverse biochemical and stress‑related traits for breeding.
The study characterizes the chloroplast‑localized protein AT4G33780 in Arabidopsis thaliana using CRISPR/Cas9 knockout and overexpression lines, revealing tissue‑specific expression and context‑dependent effects on seed germination, seedling growth, vegetative development, and root responses to nickel stress. Integrated transcriptomic (RNA‑seq) and untargeted metabolomic analyses show extensive transcriptional reprogramming—especially of cell‑wall genes—and altered central energy metabolism, indicating AT4G33780 coordinates metabolic state with developmental regulation rather than controlling single pathways.
The study examined how elevated atmospheric CO₂ (550 ppm) affects immunity in the C₄ cereal maize (Zea mays L.) by exposing plants grown under ambient and elevated CO₂ to a range of pathogens. Elevated CO₂ increased susceptibility to sugarcane mosaic virus, decreased susceptibility to several bacterial and fungal pathogens, and left susceptibility to others unchanged, with reduced bacterial disease linked to heightened basal immune responses. These findings provide a baseline for future investigations into CO₂‑responsive defense mechanisms in C₄ crops.
The study tests whether heavy‑metal stress contributed to maize domestication by exposing teosinte (Zea mays ssp. parviglumis) and the Palomero toluqueno landrace to sublethal copper and cadmium, then analysing genetic diversity, selection signatures, and transcriptomic responses of three chromosome‑5 heavy‑metal response genes (ZmHMA1, ZmHMA7, ZmSKUs5). Results reveal strong positive selection on these genes, heavy‑metal‑induced phenotypes resembling modern maize, and up‑regulation of Tb1, supporting a role for volcanic‑derived metal stress in early maize evolution.