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.

A biparental Vicia faba mapping population was screened under glasshouse conditions for resistance to a mixture of Fusarium avenaceum and Fusarium oxysporum, revealing several families with moderate to high resistance. Using the Vfaba_v2 Axiom SNP array, a high-density linkage map of 6,755 SNPs was constructed, enabling the identification of a major QTL on linkage group 4 associated with partial resistance to foot and root rot.

The study characterized 1,264 maize near‑isogenic lines derived from 18 donor inbreds crossed to the recurrent parent B73, using genotyping‑by‑sequencing and SNP‑chip data to detect 2,972 introgression segments via a novel hidden Markov model pipeline. Disease phenotyping enabled QTL mapping for foliar disease resistance, revealing extensive allelic variation among donor lines, and establishing the nNIL population as a valuable resource for dissecting complex traits in maize.