Inferring Gene Regulatory Network Architecture Underlying Complex Traits: An Integrative Analysis of Mutant Lifespan and Gene Expression Profiles Identifies Master Regulators and Key Functional Modules for Yeast Aging.

Abstract

Complex phenotypes, including aging, are influenced by a connected gene regulatory network with many interacting nodes. It has been proposed that some genes, termed "core genes," directly contribute to a trait, whereas "peripheral genes" influence the trait indirectly through network interactions. Yet demonstrating such a layered architecture and assigning genes to layers remains challenging. Using yeast aging, we developed an approach to infer network architecture underlying complex traits. Through analysis of lifespans and gene expression profiles of yeast deletion strains, we identified master regulators (MRs) whose expression change accounts for lifespan changes across mutants. Experimental tests validated 7 out of 9 MRs predicted to extend lifespan with reduced expression, and 2 out of 2 MRs predicted to extend lifespan with increased expression. We define peripheral genes as those whose effect on lifespan can be accounted for by MRs. We explored downstream mechanisms for lifespan extension by analyzing expression profiles of lifespan-extending MR mutants. We identified a set of altered functional modules-groups of core genes that work together in biological functions, such as stress response, autophagy, proteostasis, and ribosome biogenesis. These modules were validated by single-cell studies using one MR as an example. Our study reveals a network architecture where peripheral genes link to MRs, which connect to functional modules of core genes to influence lifespan, generalizing the previously proposed peripheral/core gene architecture. Our approach may be applied to analyzing complex human traits by integrating genetic perturbation vs. phenotype and expression data, such as those from GWAS and eQTL studies.