Temporal transcriptomic and proteomic profiling of causal variants in combination uncovers molecular drivers of phenotypic additivity
收藏NIAID Data Ecosystem2026-05-02 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE278267
下载链接
链接失效反馈官方服务:
资源简介:
Genetic interactions are fundamental to the architecture of complex traits, yet the molecular mechanisms by which variant combinations influence cellular pathways remain poorly understood. Here, we answer the question of whether interactions between genetic variants can activate unique pathways and if such pathways can be targeted to modulate phenotypic outcomes. The model organism Saccharomyces cerevisiae was used to dissect how two causal SNPs , MKT189G and TAO34477C, interact to modulate metabolic and phenotypic outcomes during sporulation. By integrating time-resolved transcriptomics, absolute proteomics, and targeted metabolomics in isogenic allele replacement yeast strains, we show that the combined presence of these SNPs uniquely activates the arginine biosynthesis pathway and suppresses ribosome biogenesis, reflecting a metabolic trade-off that enhances sporulation efficiency. Functional validation demonstrates that the arginine pathway is essential for mitochondrial activity and efficient sporulation only in the double-SNP background. Our findings show how genetic variant interactions can rewire core metabolic networks, providing a mechanistic framework for understanding polygenic trait regulation and the emergence of additive effects in complex traits. The wildtype Strain (SS strain) and the allele replacement strain (MMTT) were grown in sporulation medium and temporal RNA-sequencing was done at 9 different timepoints The samples were taken at 0h, 30min, 45min, 1h10min, 1h40min, 2h30min, 3h50min, 5h40min, and 8h30min . Each timepoint has 3 replicates each.
创建时间:
2025-09-03



