Exploiting the adaptation dynamics to predict the distribution of beneficial fitness effects

TL;DR

This paper investigates how the dynamics of adaptation in asexual populations can reveal the underlying distribution of beneficial fitness effects, using simulations on rugged landscapes to identify key distinguishing quantities.

Contribution

It introduces two measurable quantities that can differentiate between truncated, exponential, and power law beneficial fitness distributions during adaptation.

Findings

Fitness difference between successive mutations varies with distribution type.

Rate of fitness change over time differs across distributions.

Patterns are consistent across different mutation rates.

Abstract

Adaptation of asexual populations is driven by beneficial mutations and therefore the dynamics of this process, besides other factors, depend on the distribution of beneficial fitness effects. It is known that on uncorrelated fitness landscapes, this distribution can only be of three types: truncated, exponential and power law. We performed extensive stochastic simulations to study the adaptation dynamics on rugged fitness landscapes, and identified two quantities that can be used to distinguish the underlying distribution of beneficial fitness effects. The first quantity studied here is the fitness difference between successive mutations that spread in the population, which is found to decrease in the case of truncated distributions, remain nearly a constant for exponentially decaying distributions and increase when the fitness distribution decays as a power law. The second quantity of interest, namely, the rate of change of fitness with time also shows quantitatively different behaviour for different beneficial fitness distributions. The patterns displayed by the two aforementioned quantities are found to hold for both low and high mutation rates. We discuss how these patterns can be exploited to determine the distribution of beneficial fitness effects in microbial experiments.