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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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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. |
format | Online Article Text |
id | pubmed-5896888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
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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