Epistatic interaction maps relative to multiple metabolic phenotypes
Snitkin, Evan S.
MetadataShow full item record
Citation (published version)Evan S Snitkin, Daniel Segre. 2011. "Epistatic interaction maps relative to multiple metabolic phenotypes." PLoS Genetics, Volume 7, Issue 2, 15 pages. https://doi.org/10.1371/journal.pgen.1001294
An epistatic interaction between two genes occurs when the phenotypic impact of one gene depends on another gene, often exposing a functional association between them. Due to experimental scalability and to evolutionary significance, abundant work has been focused on studying how epistasis affects cellular growth rate, most notably in yeast. However, epistasis likely influences many different phenotypes, affecting our capacity to understand cellular functions, biochemical networks adaptation, and genetic diseases. Despite its broad significance, the extent and nature of epistasis relative to different phenotypes remain fundamentally unexplored. Here we use genome-scale metabolic network modeling to investigate the extent and properties of epistatic interactions relative to multiple phenotypes. Specifically, using an experimentally refined stoichiometric model for Saccharomyces cerevisiae, we computed a three-dimensional matrix of epistatic interactions between any two enzyme gene deletions, with respect to all metabolic flux phenotypes. We found that the total number of epistatic interactions between enzymes increases rapidly as phenotypes are added, plateauing at approximately 80 phenotypes, to an overall connectivity that is roughly 8-fold larger than the one observed relative to growth alone. Looking at interactions across all phenotypes, we found that gene pairs interact incoherently relative to different phenotypes, i.e. antagonistically relative to some phenotypes and synergistically relative to others. Specific deletion-deletion-phenotype triplets can be explained metabolically, suggesting a highly informative role of multi-phenotype epistasis in mapping cellular functions. Finally, we found that genes involved in many interactions across multiple phenotypes are more highly expressed, evolve slower, and tend to be associated with diseases, indicating that the importance of genes is hidden in their total phenotypic impact. Our predictions indicate a pervasiveness of nonlinear effects in how genetic perturbations affect multiple metabolic phenotypes. The approaches and results reported could influence future efforts in understanding metabolic diseases and the role of biochemical regulation in the cell.
RightsThis is an open-access article distributed under the terms of the Creative Commons Public Domain declaration which stipulates that, once placed in the public domain, this work may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose.
Showing items related by title, author, creator and subject.
Vaidyanathan, Prashant (2019)Synthetic genetic regulatory networks (or genetic circuits) can operate in complex biochemical environments to process and manipulate biological information to produce a desired behavior. The ability to engineer such genetic ...
Dopamine receptor genetic polymorphisms and body composition in undernourished pastoralists: an exploration of nutrition indices among nomadic and recently settled Ariaal men of northern Kenya Eisenberg, Dan T.A.; Campbell, Benjamin; Gray, Peter B.; Sorenson, Michael D. (BMC, 2008-06-10)Minor alleles of the human dopamine receptor polymorphisms, DRD2/TaqI A and DRD4/48 bp, are related to decreased functioning and/or numbers of their respective receptors and have been shown to be correlated with body mass, ...
SIVagm infection in wild African green monkeys from South Africa: epidemiology, natural history, and evolutionary considerations Ma, Dongzhu; Jasinska, Anna; Kristoff, Jan; Grobler, J. Paul; Turner, Trudy; Jung, Yoon; Schmitt, Christopher; Raehtz, Kevin; Feyertag, Felix; Sosa, Natalie Martinez; Wijewardana, Viskam; Burke, Donald S.; Robertson, David L.; Tracy, Russell; Pandrea, Ivona; Freimer, Nelson; Apetrei, Cristian (Public Library of Science, 2013-01-01)Pathogenesis studies of SIV infection have not been performed to date in wild monkeys due to difficulty in collecting and storing samples on site and the lack of analytical reagents covering the extensive SIV diversity. ...