The study re-analyzed AtGenExpress microarray data to profile expression of Arabidopsis papain-like cysteine proteases (PLCPs) and cystatins under bacterial infection, wounding, and drought, and performed in vitro assays to determine cystatin inhibition specificity for abundant PLCPs. Integrating co‑expression and inhibition data with support vector machine modeling revealed distinct PLCP‑cystatin modules for virulent versus avirulent bacterial infections and overlapping modules between drought and basal defense, indicating shared regulatory programs across stress types.

The authors compiled and standardized published data on Rubisco dark inhibition for 157 flowering plant species, categorizing them into four inhibition levels and analyzing phylogenetic trends. Their meta‑analysis reveals a complex, uneven distribution of inhibition across taxa, suggesting underlying chloroplast microenvironment drivers and providing a new resource for future photosynthesis improvement efforts.

The study examined how polyploidy, hybridization, and incomplete lineage sorting affect phylogenetic reconstructions in the genus Packera, evaluating several published paralog‑processing pipelines. Results showed that the choice of orthology and paralog handling methods markedly altered tree topology, time‑calibrated phylogenies, biogeographic histories, and detection of ancient reticulation, underscoring the need for careful methodological selection alongside comprehensive taxon sampling.

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 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.