Unravelling variant-to-function relationships in sporulation efficiency through integrative analysis of SNP-specific gene expression networks and metabolic models

Abstract

Elucidating genotype-phenotype or variant-to-function relationships remains a pivotal challenge in genetics. Specifically, understanding how genetic interactions among causal quantitative trait nucleotides (QTNs) drive phenotypic variation remains to be determined. Employing genome-scale metabolic modelling, we analysed the metabolic consequences of four causal QTNs, individually and in all combinations, responsible for modulating sporulation efficiency in yeast. Differential gene expression and network analysis revealed QTN interactions dependent changes in the connectivity of crucial metabolic regulators. Furthermore, QTN-specific metabolic models and genome-scale differential flux analysis pinpointed variations in flux across multiple metabolic pathways that could explain the observed sporulation efficiency differences. Finally, the differential regulation of the pentose phosphate pathway in specific QTN combinations suggested autophagy as a pentose phosphate pathway-dependent compensatory mechanism for yeast sporulation. Our study contributes to the evolving functional understanding of variants, providing insightful information into the mechanisms governing phenotypic variation.