Protein-protein interactions are a major source of epistasis in genetic interaction networks

Genetic interaction and protein-protein interaction networks have proved among the most important tools for inference of gene function and genotype-phenotype relationship. It remains unclear, however, how these two networks are related to each other. Here we demonstrate that the strengths of epistatic genetic interactions between two genes strongly correlate with the binding free energies of interactions between their cognate proteins, for both yeast and human genomes. Consequently, we show that genetic interaction and protein-protein interaction networks can reciprocally predict each other. Further, we observe that functional divergence and redundancy in duplicated genes (paralogs) are reflected in the binding affinity of their interactions with other proteins and in their genetic interaction strengths. Finally, we demonstrate that the overall topologies of genetic interaction and protein-protein interaction networks significantly overlap in two topological features: modules, in which genes/proteins are organized by common function, and connectors, which link modules to each other. This opens avenues for integrated network approaches in understanding cellular processes and flow of genomic information.

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Publication Details

Journal
Nature Communications
Published
2026-02-05
DOI
https://doi.org/10.1038/s41467-026-69152-2
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
0.00

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article

Protein-protein interactions are a major source of epistasis in genetic interaction networks

Xavier Castellanos-Girouard, Stephen W. Michnick
Nature Communications
Bioinformatics and Genomic Networks
article

Protein-protein interactions are a major source of epistasis in genetic interaction networks

Xavier Castellanos-Girouard, Stephen W. Michnick
article en

Abstract

Genetic interaction and protein-protein interaction networks have proved among the most important tools for inference of gene function and genotype-phenotype relationship. It remains unclear, however, how these two networks are related to each other. Here we demonstrate that the strengths of epistatic genetic interactions between two genes strongly correlate with the binding free energies of interactions between their cognate proteins, for both yeast and human genomes. Consequently, we show that genetic interaction and protein-protein interaction networks can reciprocally predict each other. Further, we observe that functional divergence and redundancy in duplicated genes (paralogs) are reflected in the binding affinity of their interactions with other proteins and in their genetic interaction strengths. Finally, we demonstrate that the overall topologies of genetic interaction and protein-protein interaction networks significantly overlap in two topological features: modules, in which genes/proteins are organized by common function, and connectors, which link modules to each other. This opens avenues for integrated network approaches in understanding cellular processes and flow of genomic information.

Nature CommunicationsVol. 17(1)
Wellcome Sanger Institute (GB), Université de Montréal (CA)
Canada Research Chairs, Canadian Institutes of Health Research, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 66%
Bioinformatics and Genomic Networks
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