The genetic landscape of a physical interaction

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  • dc.contributor.author Diss, Guillaume
  • dc.contributor.author Lehner, Ben, 1978-
  • dc.date.accessioned 2019-11-13T11:18:54Z
  • dc.date.available 2019-11-13T11:18:54Z
  • dc.date.issued 2018
  • dc.description.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.
  • dc.description.sponsorship 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.
  • dc.format.mimetype application/pdf
  • dc.identifier.citation Diss G, Lehner B. The genetic landscape of a physical interaction. eLife. 2018;7:e32472. DOI: 10.7554/eLife.32472
  • dc.identifier.doi http://dx.doi.org/10.7554/eLife.32472
  • dc.identifier.issn 2050-084X
  • dc.identifier.uri http://hdl.handle.net/10230/42840
  • dc.language.iso eng
  • dc.publisher eLife
  • dc.relation.ispartof eLife. 2018;7:e32472
  • dc.relation.projectID info:eu-repo/grantAgreement/EC/FP7/616434
  • dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/BFU2011-26206
  • dc.rights © 2018, Diss et al. This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use and redistribution provided that the original author and source are credited.
  • dc.rights.accessRights info:eu-repo/semantics/openAccess
  • dc.rights.uri http://creativecommons.org/licenses/by/4.0/
  • dc.subject.keyword S. cerevisiae
  • dc.subject.keyword Computational biology
  • dc.subject.keyword Deep mutagenesis
  • dc.subject.keyword Epistasis
  • dc.subject.keyword Genetic interaction
  • dc.subject.keyword Human
  • dc.subject.keyword Protein interactions
  • dc.subject.keyword Systems biology
  • dc.subject.keyword Transcription factors
  • dc.title The genetic landscape of a physical interaction
  • dc.type info:eu-repo/semantics/article
  • dc.type.version info:eu-repo/semantics/publishedVersion