Mutation–selection models solved exactly with methods of statistical mechanics

Модели мутации–отбора, точно решаемые методами статистической механики
Ellen Baake, Holger Wagner
2001-08-01

Ising quantum chainerror thresholdmutation loadmutation–selection modelsquantum statistical mechanics
We reconsider deterministic models of mutation and selection acting on populations of sequences, or, equivalently, multilocus systems with complete linkage. Exact analytical results concerning such systems are few, and we present recent and new ones obtained with the help of methods from quantum statistical mechanics. We consider a continuous-time model for an infinite population of haploids (or diploids without dominance), with N sites each, two states per site, symmetric mutation and arbitrary fitness function. We show that this model is exactly equivalent to a so-called Ising quantum chain. In this picture, fitness corresponds to the interaction energy of spins, and mutation to a temperature-like parameter. The highly elaborate methods of statistical mechanics allow one to find exact solutions for non-trivial examples. These include quadratic fitness functions, as well as 'Onsager's landscape'. The latter is a fitness function which captures some essential features of molecular evolution, such as neutrality, compensatory mutations and flat ridges. We investigate the mean number of mutations, the mutation load, and the variance in fitness under mutation-selection balance. This also yields some insight into the 'error threshold' phenomenon, which occurs in some, but not all, examples.
1
Exact solutions are obtained for nontrivial landscapes, including quadratic fitness functions and Onsager’s landscape.
2
In the statistical-mechanics mapping, fitness acts as spin interaction energy, while mutation corresponds to a temperature-like parameter.
3
Onsager’s landscape models evolutionary features including neutrality, compensatory mutations, and flat fitness ridges.
4
The continuous-time mutation–selection model is exactly equivalent to an Ising quantum chain for haploid populations with symmetric mutation and arbitrary fitness.
5
The framework calculates mutation number, mutation load, and fitness variance at mutation–selection balance, clarifying why error thresholds occur in some but not all landscapes.

Deterministic mutation–selection systems for infinite populations of haploid sequences (or completely linked multilocus systems) with N two-state sites

Exact mutation–selection balance properties, including mean mutation number, mutation load, fitness variance, and the occurrence of the error threshold, under symmetric mutation and arbitrary fitness functions

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2001-08-01
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Ellen Baake
Holger Wagner
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