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The strength of genetic interactions scales weakly with mutational effects
BACKGROUND: Genetic interactions pervade every aspect of biology, from evolutionary theory, where they determine the accessibility of evolutionary paths, to medicine, where they can contribute to complex genetic diseases. Until very recently, studies on epistatic interactions have been based on a ha...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053755/ https://www.ncbi.nlm.nih.gov/pubmed/23889884 http://dx.doi.org/10.1186/gb-2013-14-7-r76 |
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author | Velenich, Andrea Gore, Jeff |
author_facet | Velenich, Andrea Gore, Jeff |
author_sort | Velenich, Andrea |
collection | PubMed |
description | BACKGROUND: Genetic interactions pervade every aspect of biology, from evolutionary theory, where they determine the accessibility of evolutionary paths, to medicine, where they can contribute to complex genetic diseases. Until very recently, studies on epistatic interactions have been based on a handful of mutations, providing at best anecdotal evidence about the frequency and the typical strength of genetic interactions. In this study, we analyze a publicly available dataset that contains the growth rates of over five million double knockout mutants of the yeast Saccharomyces cerevisiae. RESULTS: We discuss a geometric definition of epistasis that reveals a simple and surprisingly weak scaling law for the characteristic strength of genetic interactions as a function of the effects of the mutations being combined. We then utilized this scaling to quantify the roughness of naturally occurring fitness landscapes. Finally, we show how the observed roughness differs from what is predicted by Fisher's geometric model of epistasis, and discuss the consequences for evolutionary dynamics. CONCLUSIONS: Although epistatic interactions between specific genes remain largely unpredictable, the statistical properties of an ensemble of interactions can display conspicuous regularities and be described by simple mathematical laws. By exploiting the amount of data produced by modern high-throughput techniques, it is now possible to thoroughly test the predictions of theoretical models of genetic interactions and to build informed computational models of evolution on realistic fitness landscapes. |
format | Online Article Text |
id | pubmed-4053755 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-40537552014-06-12 The strength of genetic interactions scales weakly with mutational effects Velenich, Andrea Gore, Jeff Genome Biol Research BACKGROUND: Genetic interactions pervade every aspect of biology, from evolutionary theory, where they determine the accessibility of evolutionary paths, to medicine, where they can contribute to complex genetic diseases. Until very recently, studies on epistatic interactions have been based on a handful of mutations, providing at best anecdotal evidence about the frequency and the typical strength of genetic interactions. In this study, we analyze a publicly available dataset that contains the growth rates of over five million double knockout mutants of the yeast Saccharomyces cerevisiae. RESULTS: We discuss a geometric definition of epistasis that reveals a simple and surprisingly weak scaling law for the characteristic strength of genetic interactions as a function of the effects of the mutations being combined. We then utilized this scaling to quantify the roughness of naturally occurring fitness landscapes. Finally, we show how the observed roughness differs from what is predicted by Fisher's geometric model of epistasis, and discuss the consequences for evolutionary dynamics. CONCLUSIONS: Although epistatic interactions between specific genes remain largely unpredictable, the statistical properties of an ensemble of interactions can display conspicuous regularities and be described by simple mathematical laws. By exploiting the amount of data produced by modern high-throughput techniques, it is now possible to thoroughly test the predictions of theoretical models of genetic interactions and to build informed computational models of evolution on realistic fitness landscapes. BioMed Central 2013 2013-07-26 /pmc/articles/PMC4053755/ /pubmed/23889884 http://dx.doi.org/10.1186/gb-2013-14-7-r76 Text en Copyright © 2013 Velenich et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Velenich, Andrea Gore, Jeff The strength of genetic interactions scales weakly with mutational effects |
title | The strength of genetic interactions scales weakly with mutational effects |
title_full | The strength of genetic interactions scales weakly with mutational effects |
title_fullStr | The strength of genetic interactions scales weakly with mutational effects |
title_full_unstemmed | The strength of genetic interactions scales weakly with mutational effects |
title_short | The strength of genetic interactions scales weakly with mutational effects |
title_sort | strength of genetic interactions scales weakly with mutational effects |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053755/ https://www.ncbi.nlm.nih.gov/pubmed/23889884 http://dx.doi.org/10.1186/gb-2013-14-7-r76 |
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