We consider a population evolving due to mutation, selection , genetic drift and recombination, where selection is only two-loci terms (pairwise epistatic fitness). We further consider the problem of inferring fitness in the evolutionary dynamics from one or several snap-shots of the distribution of genotypes in the population. We show that this is possible using a recently developed theory that relates parameters of such a distribution to parameters of the evolutionary dynamics. This extends classical results on the Quasi-Linkage Equilibrium (QLE) regime first obtained by Kimura , and more recently studied by Neher and Shraiman. In particular, the new theory outperforms the Kimura-Neher-Shraiman theory in the interesting regime where the effects of mutations are comparable to or larger than recombination. Additionally, it can work when recombination is absent. The findings are validated through numerical simulations.
We consider a population evolving due to mutation, selection and recombination, where selection includes single-locus terms (additive fitness) and two-loci terms (pairwise epistatic fitness). We further consider the problem of inferring fitness in the evolutionary dynamics from one or several snap-shots of the distribution of genotypes in the population. In the recent literature this has been done by applying the Quasi-Linkage Equilibrium (QLE) regime first obtained by Kimura in the limit of high recombination. Here we show that the approach also works in the interesting regime where the effects of mutations are comparable to or larger than recombination. This leads to a modified main epistatic fitness inference formula where the rates of mutation and recombination occur together. We also derive this formula using by a previously developed Gaussian closure that formally remains valid when recombination is absent. The findings are validated through numerical simulations.
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, genetic drift
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is only
includes single-locus terms (additive fitness) and
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We show that this is possible using a recently developed theory that relates parameters of such a distribution to parameters of the evolutionary dynamics. This extends classical results on the
In the recent literature this has been done by applying the
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, and more recently studied by Neher and Shraiman. In particular, the new theory outperforms the Kimura-Neher-Shraiman theory
in the limit of high recombination. Here we show that the approach also works
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Additionally, it can work
This leads to a modified main epistatic fitness inference formula where the rates of mutation and recombination occur together. We also derive this formula using by a previously developed Gaussian closure that formally remains valid