Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories

Lyons, Daniel M.; Zou, Zhengting; Xu, Haiqing; Zhang, Jianzhi

doi:10.1038/s41559-020-01286-y

Cited by 59 publications

(57 citation statements)

References 43 publications

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“…Here, we show that diminishing-returns and increasing-costs epistasis are a simple consequence of widespread epistasis. This is consistent with recent work [16] that proposes a similar argument to explain these phenomena. However, while the core idea is similar, we present here an alternative framework based on the Fourier analysis of fitness landscapes, which leads to new insights and quantitative predictions.…”

Section: Introductionsupporting

confidence: 94%

Global epistasis emerges from a generic model of a complex trait

Reddy¹,

Desai

2020

Preprint

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Epistasis between mutations can make adaptation contingent on evolutionary history. Yet despite widespread "microscopic" epistasis between the mutations involved, microbial evolution experiments show consistent patterns of fitness increases during laboratory adaptation. Recent work has found 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 more-fit genetic backgrounds. This global "macroscopic" epistasis is thought to make phenotypic evolution repeatable, even while the genetic basis of this evolution is highly stochastic. However, the mechanistic basis of consistent macroscopic epistasis remains unknown. Here we show, using a generic model of a complex trait, that global diminishing-returns and increasing-costs epistasis arise naturally as a consequence of pervasive microscopic epistasis, emerging simply as a statistical trend due to an imbalance between positive and negative contributions to the fitness. 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 also describe the predictions of this model for the patterns of fitness evolution and for how the distribution of fitness e↵ects shifts as a population adapts, and propose additional experimental tests of these results. ⇤

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Section: Introductionsupporting

confidence: 94%

Global epistasis emerges from a generic model of a complex trait

Reddy¹,

Desai

2020

Preprint

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“…Yet, how epistasis emerges from the molecular architecture of the cell and how it propagates to higher-level phenotypes, such as fitness, remains largely unknown. Several recent studies made a statistical argument that the structure of the fitness landscape (and, as a consequence, the epistatic interactions between mutations at the level of fitness) may be largely independent of the underlying molecular architecture of the organism ( Martin, 2014 ; Lyons et al, 2020 ; Reddy and Desai, 2020 ). If mutations are typically highly pleiotropic (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…The reasons for these patterns are currently unclear. Several recent theoretical papers offer possible statistical explanations for them ( Martin, 2014 ; Lyons et al, 2020 ; Reddy and Desai, 2020 ). On the other hand, mechanistic predictions for the distribution of epistasis coefficients are not yet available (but see Sanjuán and Nebot, 2008 ; Macía et al, 2012 ; Chiu et al, 2012 ).…”

Section: Discussionmentioning

confidence: 99%

Emergence and propagation of epistasis in metabolic networks

Kryazhimskiy

2021

eLife

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Epistasis is often used to probe functional relationships between genes, and it plays an important role in evolution. However, we lack theory to understand how functional relationships at the molecular level translate into epistasis at the level of whole-organism phenotypes, such as fitness. Here, I derive two rules for how epistasis between mutations with small effects propagates from lower- to higher-level phenotypes in a hierarchical metabolic network with first-order kinetics and how such epistasis depends on topology. Most importantly, weak epistasis at a lower level may be distorted as it propagates to higher levels. Computational analyses show that epistasis in more realistic models likely follows similar, albeit more complex, patterns. These results suggest that pairwise inter-gene epistasis should be common and it should generically depend on the genetic background and environment. Furthermore, the epistasis coefficients measured for high-level phenotypes may not be sufficient to fully infer the underlying functional relationships.

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“…Yet, how epistasis emerges from the molecular architecture of the cell and how it propagates to higher-level phenotypes, such as fitness, remains largely unknown. Several recent studies made a statistical argument that the structure of the fitness landscape (and, as a consequence, the epistatic interactions between mutations at the level of fitness) may be largely independent of the underlying molecular architecture of the organism (Martin, 2014;Lyons et al, 2020;Reddy and Desai, 2020).…”

Section: Discussionmentioning

confidence: 99%

“…The reasons for these patterns are currently unclear. Several recent theoretical papers offer possible statistical explanations for them (Martin, 2014;Lyons et al, 2020;Reddy and Desai, 2020). On the other hand, mechanistic predictions for the distribution of epistasis coefficients are not yet available (but see Sanjuán and Nebot, 2008;Macía et al, 2012;Chiu et al, 2012).…”

Section: Skew In the Distribution Of Epistasis Coefficientsmentioning

confidence: 99%

Emergence and Propagation of Epistasis in Metabolic Networks

Kryazhimskiy

2020

Preprint

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AbstractGenome-wide measurements of epistasis are often used to probe functional relationships between genes. However, we lack a theory for understanding how functional relationships at the molecular level translate into epistasis measured at the level of whole-organism phenotypes, such as fitness. Here, I develop a mathematical model of a hierarchical metabolic network to address this gap. I derive how the topological relationship between reactions affected by mutations translates into epistasis and how this epistasis propagates from lower- to higher-level phenotypes in the network. An analysis of a computational model of glycolysis indicates that epistasis in more realistic metabolic networks follows similar albeit more complex patterns. These results imply that epistasis coefficients measured for high-level phenotypes carry some but not all information about the underlying functional relationships between gene products. They also suggest that pairwise inter-gene epistasis should be common and should depend on the genetic background and environment.

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Idiosyncratic epistasis creates universals in mutational effects and evolutionary trajectories

Cited by 59 publications

References 43 publications

Global epistasis emerges from a generic model of a complex trait

Global epistasis emerges from a generic model of a complex trait

Emergence and propagation of epistasis in metabolic networks

Emergence and Propagation of Epistasis in Metabolic Networks

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