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 provides an in‑depth proteomic characterization of brewer's spent grain (BSG) and tracks proteome dynamics during malting and mashing, revealing that 29% of identified proteins change in abundance and that B3‑Hordein dominates the BSG protein pool. BSG contains a high proportion of intracellular proteins and over 45% of its proteins are potential allergens or antinutritional factors, underscoring the need for targeted downstream processing to create safe, functional food ingredients.

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.

The study profiled the Arabidopsis apoplastic proteome during pattern‑triggered immunity induced by the flg22 peptide, using apoplastic washing fluid with minimal cytoplasmic contamination followed by LC‑MS/MS. Results showed consistent PTI‑specific enrichment and depletion of peptides, a bias toward ectodomain peptides of receptor‑like kinases, and increased abundance of the exosome marker tetraspanin 8, indicating heightened exosome levels during PTI.