Weakest link epistasis and the geometry of genetic load

Labourel, Florian JF, Bansept, Florence, McCandlish, David M (January 2026) Weakest link epistasis and the geometry of genetic load. bioRxiv. ISSN 2692-8205 (Submitted)

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Abstract

Because natural selection must optimise multiple traits at once, previous work has suggested that phenotypic dimensionality can substantially worsen the equilibrium fitness defect of a population relative to the phenotypic optimum. However, it remains unclear how conclusions drawn from classical theoretical phenotype–fitness maps extend to models grounded in explicit biological mechanisms. Here we introduce weakest-link epistasis (WLE), a framework in which fitness is determined by the least-fit phenotypic component, an extreme form of diminishing returns epistasis. We show that in this framework, increasing dimensionality amplifies the load in a manner comparable to, but surprisingly not more than, Fisher’s geometric model (FGM). Building on this similarity, we demonstrate why genetic load is often invariant across different rules for combining trait-specific fitness components into an overall organismal fitness. We explore these ideas by considering the family of models where the organismal fitness is determined based on the ℓp-norm of the vector of trait-specific fitness defects, a framework that includes both FGM and WLE, but also captures a continuum of genetic architectures, ranging from generalist to specialist regimes. Altogether, our approach proposes a new perspective on the geometry of adaptive landscapes, and may help provide quantitative insight into the cost of complexity.

Item Type:	Paper
Subjects:	bioinformatics bioinformatics > quantitative biology bioinformatics > quantitative biology > quantitative genetics > quantitative epistasis bioinformatics > quantitative biology > quantitative genetics
CSHL Authors:	McCandlish, David
Communities:	CSHL labs > McCandlish lab
SWORD Depositor:	CSHL Elements
Depositing User:	CSHL Elements
Date:	27 January 2026
Date Deposited:	12 Feb 2026 13:06
Last Modified:	12 Feb 2026 13:06
PMCID:	PMC12822725
Related URLs:	Publisher
URI:	https://repository.cshl.edu/id/eprint/42075

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