Gene epistasis influences metabolism of Saccharomyces Cerevisiae

Epistasis, the interaction of genes in a non-additive manner is crucial for understanding changes in gene expression. By using public data from yeast metabolic mutants we explored the effect of epistasis in metabolism. By employing additive models as a null hypothesis, we analyzed differential gene expression in double mutants compared to single mutants and wild-type strains to isolate epistatic interactions. Specifically, we focused on genes differentially expressed in HL double mutants, which were not explained by single mutants H or L. Our analyses, which integrated metabolomics, proteomics, and transcriptomics data, identified a set of candidate genes affected by epistatic interactions. These genes were characterized through protein-protein interaction networks and gene regulatory networks, revealing notable correlations and structural differences at the proteomics level. Principal Component Analysis (PCA) and Partial Least Squares (PLS) indicated variable reproducibility in metabolomics data, but a strong explanatory power for epistatic genes relative to the transcriptome.