The study demonstrates that mutating maize A-type cyclin genes homologous to Arabidopsis TAM induces the formation of diploid gametes with high efficiency, leading to tetraploid progeny. This provides a viable apomeiosis component for synthetic apomixis in maize, complementing existing parthenogenesis approaches.

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 shows that the SnRK1 catalytic subunit KIN10 directs tissue-specific growth‑defense programs in Arabidopsis thaliana by reshaping transcriptomes. kin10 knockout mutants exhibit altered root transcription, reduced root growth, and weakened defense against Pseudomonas syringae, whereas KIN10 overexpression activates shoot defense pathways, increasing ROS and salicylic acid signaling at the cost of growth.

The study examined how sudden changes in non‑saturating light intensity affect photosynthetic efficiency in the C4 crop maize (Zea mays) by measuring photosynthetic rates and metabolite pools over time. Decreases in irradiance caused transient buffering via large intercellular shuttle metabolites, but the system fell into a sub‑optimal metabolic state that required minutes to recover, while increases in irradiance produced delayed steady‑state photosynthesis due to enzyme regulation and the need to replenish metabolite pools, with CO2 back‑leakage and photorespiration further reducing efficiency.

The study finely dissected shoot stem cell–enriched tissues from maize and Arabidopsis thaliana and optimized single‑cell RNA‑seq protocols to reliably capture CLAVATA3 and WUSCHEL‑expressing cells. Cross‑species comparison and functional validation, including spatial transcriptomics and mutant analyses, revealed conserved ribosome‑associated RNA‑binding proteins and sugar‑kinase families as key regulators linked to shoot development and yield traits.

Low red to far‑red (R:FR) light ratios increase the priming of herbivore‑induced volatile emissions in maize plants that have been exposed to neighbor volatiles, regardless of the light conditions of the emitting plants. Both constitutive VOCs and HIPVs released by maize grown under low R:FR amplify HIPV emission in neighboring receivers, indicating that canopy shade can intensify volatile‑mediated plant‑plant communication.

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 mapped the macroscopic and cellular development of maize leaves and internodes, revealing a shared growth design with organ‑specific timing. Using high‑resolution spatiotemporal transcriptome profiling of 272 tissue samples under well‑watered and drought conditions, the authors generated a searchable expression atlas and identified conserved and organ‑specific gene regulatory patterns, including genes linked to leaf angle and vascular development. This resource advances understanding of shoot organ development and drought response for targeted trait engineering in maize.

The study introduces an in-soil fiber Bragg grating (FBG) sensing system that continuously records three-dimensional strain from growing pseudo-roots, enabling non‑destructive monitoring of root architecture. Using two ResNet models, the system predicts root width and depth with over 90% accuracy, and performance improves to 96‑98% after retraining on data from actual corn (Zea mays) roots over a 30‑day period. This prototype demonstrates potential for scalable, real‑time root phenotyping and broader soil environment sensing.

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.