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The genetic landscape of a physical interaction

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 t...

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Detalles Bibliográficos
Autores principales: Diss, Guillaume, Lehner, Ben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896888/
https://www.ncbi.nlm.nih.gov/pubmed/29638215
http://dx.doi.org/10.7554/eLife.32472
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author Diss, Guillaume
Lehner, Ben
author_facet Diss, Guillaume
Lehner, Ben
author_sort Diss, Guillaume
collection PubMed
description 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.
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spelling pubmed-58968882018-04-16 The genetic landscape of a physical interaction Diss, Guillaume Lehner, Ben eLife Computational and Systems Biology 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. eLife Sciences Publications, Ltd 2018-04-11 /pmc/articles/PMC5896888/ /pubmed/29638215 http://dx.doi.org/10.7554/eLife.32472 Text en © 2018, Diss et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/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.
spellingShingle Computational and Systems Biology
Diss, Guillaume
Lehner, Ben
The genetic landscape of a physical interaction
title The genetic landscape of a physical interaction
title_full The genetic landscape of a physical interaction
title_fullStr The genetic landscape of a physical interaction
title_full_unstemmed The genetic landscape of a physical interaction
title_short The genetic landscape of a physical interaction
title_sort genetic landscape of a physical interaction
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896888/
https://www.ncbi.nlm.nih.gov/pubmed/29638215
http://dx.doi.org/10.7554/eLife.32472
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