Epistasis between mutations makes adaptation contingent on evolutionary history. Yet despite widespread 'microscopic' epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increase between replicate lines. Recent work shows that this consistency is driven in part by global patterns of diminishing-returns and increasing-costs epistasis, which make mutations systematically less beneficial (or more deleterious) on fitter genetic backgrounds. However, the origin of this 'global' epistasis remains unknown. Here we show that diminishing-returns and increasing-costs epistasis emerge generically as a consequence of pervasive microscopic epistasis. Our model predicts a specific quantitative relationship between the magnitude of global epistasis and the stochastic effects of microscopic epistasis, which we confirm by re-analyzing existing data. We further show that the distribution of fitness effects has a universal form when epistasis is widespread, and introduce a novel fitness landscape model to show how phenotypic evolution can be repeatable despite sequence-level stochasticity.
The code and data used to generate the figures are available at https://github.com/greddy992/global_epistasis.
Long-term dynamics of adaptation in asexual populationsDOI: 10.1126/science.1243357.
Global epistasis makes adaptation predictable despite sequence-level stochasticityDOI: 10.1126/science.1250939.
Higher-fitness yeast genotypes are less robust to deleterious mutationsDOI: 10.1126/science.aay4199.
- Gautam Reddy
- Michael M Desai
- Michael M Desai
- Michael M Desai
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Naama Barkai, Weizmann Institute of Science, Israel
© 2021, Reddy & Desai
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Changes in an organism’s environment, genome, or gene expression patterns can lead to changes in its metabolism. The metabolic phenotype can be under selection and contributes to adaptation. However, the networked and convoluted nature of an organism’s metabolism makes relating mutations, metabolic changes, and effects on fitness challenging. To overcome this challenge, we use the long-term evolution experiment (LTEE) with E. coli as a model to understand how mutations can eventually affect metabolism and perhaps fitness. We used mass spectrometry to broadly survey the metabolomes of the ancestral strains and all 12 evolved lines. We combined this metabolic data with mutation and expression data to suggest how mutations that alter specific reaction pathways, such as the biosynthesis of nicotinamide adenine dinucleotide, might increase fitness in the system. Our work provides a better understanding of how mutations might affect fitness through the metabolic changes in the LTEE and thus provides a major step in developing a complete genotype–phenotype map for this experimental system.
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