Stable maintenance of hidden switches as a strategy to increase the gene expression stability
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Embargo End Date:
2021-07-14
Type
ArticleAuthors
Kuwahara, Hiroyuki
Gao, Xin

KAUST Department
Computational Bioscience Research Center (CBRC)Computer Science Program
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
KAUST Grant Number
BAS/1/1624-01FCC/1/1976-18
FCC/1/1976-23
FCC/1/1976-25
FCC/1/1976-26
URF/1/3412-01
URF/1/3450-01
Date
2021-01-14Embargo End Date
2021-07-14Submitted Date
2020-05-30Permanent link to this record
http://hdl.handle.net/10754/667208
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In response to severe genetic and environmental perturbations, wild-type organisms can express hidden alternative phenotypes adaptive to such adverse conditions. While our theoretical understanding of the population-level fitness advantage and evolution of phenotypic switching under variable environments has grown, the mechanism by which these organisms maintain phenotypic switching capabilities under static environments remains to be elucidated. Here, using computational simulations, we analyzed the evolution of gene circuits under natural selection and found that different strategies evolved to increase the gene expression stability near the optimum level. In a population comprising bistable individuals, a strategy of maintaining bistability and raising the potential barrier separating the bistable regimes was consistently taken. Our results serve as evidence that hidden bistable switches can be stably maintained during environmental stasis—an essential property enabling the timely release of adaptive alternatives with small genetic changes in the event of substantial perturbations.Citation
Kuwahara, H., & Gao, X. (2021). Stable maintenance of hidden switches as a strategy to increase the gene expression stability. Nature Computational Science, 1(1), 62–70. doi:10.1038/s43588-020-00001-ySponsors
We thank O. Soyer and T. Gojobori for their comments on an earlier version of the manuscript. X.G. was supported by the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under award numbers BAS/1/1624-01, URF/1/3412-01, URF/1/3450-01, FCC/1/1976-18, FCC/1/1976-23, FCC/1/1976-25, FCC/1/1976-26 and FCS/1/4102-02.Publisher
Springer Science and Business Media LLCJournal
Nature Computational ScienceAdditional Links
http://www.nature.com/articles/s43588-020-00001-yae974a485f413a2113503eed53cd6c53
10.1038/s43588-020-00001-y