The genetic landscape of a physical interaction

Abstract

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay - deepPCA - we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes - interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions.This work was supported by a European Research Council (ERC) Consolidator grant (616434), the Spanish Ministry of Economy and Competitiveness (BFU2011-26206 and ‘Centro de Excelencia Severo Ochoa' SEV-2012–0208), the AXA Research Fund, the Bettencourt Schueller Foundation, Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR, SGR-831), the EMBL-CRG Systems Biology Program, and the CERCA Program/Generalitat de Catalunya. GD is a non-stipendiary EMBO Fellow and a Marie-Curie Fellow under grant agreement 608959