A High-Order Cumulant Extension of Quasi-Linkage Equilibrium
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arXiv
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| Format: | Preprint |
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2025
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| author | Shimagaki, Kai S. Fernandez-de-Cossio-Diaz, Jorge Pastore, Mauro Monasson, Rémi Cocco, Simona Barton, John P. |
| author_facet | Shimagaki, Kai S. Fernandez-de-Cossio-Diaz, Jorge Pastore, Mauro Monasson, Rémi Cocco, Simona Barton, John P. |
| contents | A central question in evolutionary biology is how to quantitatively understand the dynamics of genetically diverse populations. Modeling the genotype distribution is challenging, as it ultimately requires tracking all correlations (or cumulants) among alleles at different loci. The quasi-linkage equilibrium (QLE) approximation simplifies this by assuming that correlations between alleles at different loci are weak -- i.e., low linkage disequilibrium -- allowing their dynamics to be modeled perturbatively. However, QLE breaks down under strong selection, significant epistatic interactions, or weak recombination. We extend the multilocus QLE framework to allow cumulants up to order $K$ to evolve dynamically, while higher-order cumulants ($>K$) are assumed to equilibrate rapidly. This extended QLE (exQLE) framework yields a general equation of motion for cumulants up to order $K$, which parallels the standard QLE dynamics (recovered when $K = 1$). In this formulation, cumulant dynamics are driven by the gradient of average fitness, mediated by a geometrically interpretable matrix that stems from competition among genotypes. Our analysis shows that the exQLE with $K=2$ accurately captures cumulant dynamics even when the fitness function includes higher-order (e.g., third- or fourth-order) epistatic interactions, capabilities that standard QLE lacks. We also applied the exQLE framework to infer fitness parameters from temporal sequence data. Overall, exQLE provides a systematic and interpretable approximation scheme, leveraging analytical cumulant dynamics and reducing complexity by progressively truncating higher-order cumulants. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2509_10987 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A High-Order Cumulant Extension of Quasi-Linkage Equilibrium Shimagaki, Kai S. Fernandez-de-Cossio-Diaz, Jorge Pastore, Mauro Monasson, Rémi Cocco, Simona Barton, John P. Populations and Evolution Computation A central question in evolutionary biology is how to quantitatively understand the dynamics of genetically diverse populations. Modeling the genotype distribution is challenging, as it ultimately requires tracking all correlations (or cumulants) among alleles at different loci. The quasi-linkage equilibrium (QLE) approximation simplifies this by assuming that correlations between alleles at different loci are weak -- i.e., low linkage disequilibrium -- allowing their dynamics to be modeled perturbatively. However, QLE breaks down under strong selection, significant epistatic interactions, or weak recombination. We extend the multilocus QLE framework to allow cumulants up to order $K$ to evolve dynamically, while higher-order cumulants ($>K$) are assumed to equilibrate rapidly. This extended QLE (exQLE) framework yields a general equation of motion for cumulants up to order $K$, which parallels the standard QLE dynamics (recovered when $K = 1$). In this formulation, cumulant dynamics are driven by the gradient of average fitness, mediated by a geometrically interpretable matrix that stems from competition among genotypes. Our analysis shows that the exQLE with $K=2$ accurately captures cumulant dynamics even when the fitness function includes higher-order (e.g., third- or fourth-order) epistatic interactions, capabilities that standard QLE lacks. We also applied the exQLE framework to infer fitness parameters from temporal sequence data. Overall, exQLE provides a systematic and interpretable approximation scheme, leveraging analytical cumulant dynamics and reducing complexity by progressively truncating higher-order cumulants. |
| title | A High-Order Cumulant Extension of Quasi-Linkage Equilibrium |
| topic | Populations and Evolution Computation |
| url | https://arxiv.org/abs/2509.10987 |