Functional bottlenecks can emerge from non-epistatic underlying traits

Protein fitness landscapes frequently exhibit epistasis, where the effect of a mutation depends on the genetic context in which it occurs, i.e., the rest of the protein sequence. Epistasis increases landscape complexity, often resulting in multiple fitness peaks. In its simplest form, known as global epistasis, fitness is modeled as a non-linear function of an underlying additive trait. In contrast, more complex epistasis arises from a network of (pairwise or many-body) interactions between residues, which cannot be removed by a single non-linear transformation. Recent studies have explored how global and network epistasis contribute to the emergence of functional bottlenecks - fitness landscape topologies where two broad high-fitness basins, representing distinct phenotypes, are separated by a bottleneck that can only be crossed via one or a few mutational paths. Here, we introduce and analyze a stylized model of global epistasis with an additive underlying trait. We demonstrate that functional bottlenecks arise with high probability if the model is properly calibrated. Furthermore, our results underscore that a proper balance between neutral and non-neutral mutations is needed for the emergence of functional bottlenecks.

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Journal
PLoS Computational Biology
Published
2026-03-16
DOI
https://doi.org/10.1371/journal.pcbi.1014000
Primary Topic
Adipose Tissue and Metabolism
Type
article
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article

Functional bottlenecks can emerge from non-epistatic underlying traits

A. Schulte, Francesco Zamponi, Samar Alqatari, Saverio Rossi
PLoS Computational Biology
Adipose Tissue and Metabolism
article

Functional bottlenecks can emerge from non-epistatic underlying traits

A. Schulte, Francesco Zamponi, Samar Alqatari, Saverio Rossi
article en

Abstract

Protein fitness landscapes frequently exhibit epistasis, where the effect of a mutation depends on the genetic context in which it occurs, i.e., the rest of the protein sequence. Epistasis increases landscape complexity, often resulting in multiple fitness peaks. In its simplest form, known as global epistasis, fitness is modeled as a non-linear function of an underlying additive trait. In contrast, more complex epistasis arises from a network of (pairwise or many-body) interactions between residues, which cannot be removed by a single non-linear transformation. Recent studies have explored how global and network epistasis contribute to the emergence of functional bottlenecks - fitness landscape topologies where two broad high-fitness basins, representing distinct phenotypes, are separated by a bottleneck that can only be crossed via one or a few mutational paths. Here, we introduce and analyze a stylized model of global epistasis with an additive underlying trait. We demonstrate that functional bottlenecks arise with high probability if the model is properly calibrated. Furthermore, our results underscore that a proper balance between neutral and non-neutral mutations is needed for the emergence of functional bottlenecks.

PLoS Computational BiologyVol. 22(3)
University of Chicago (US), Sapienza University of Rome (IT)
Openalex Percentile: Top 100%
Adipose Tissue and Metabolism
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Functional bottlenecks can emerge from non-epistatic underlying traits — A. Schulte, Francesco Zamponi, et al. · PLoS Computational Biology (2026) | TGRS Research Map | TGRS