Selection-Like Biases Emerge in Population Models with Recurrent Jackpot Events

Area of Science:

• Evolutionary biology
• Population genetics
• Theoretical biology

Background:

• Evolutionary dynamics out of equilibrium can produce skewed descendant number distributions.
• Luria and Delbrück identified "jackpot" events as instances where early or fit ancestors have disproportionately many descendants.

Purpose of the Study:

• To investigate how recurrent "jackpot" events influence allele frequency dynamics.
• To determine if these events create a selection-like bias and understand its characteristics.

Main Methods:

• Analysis of allele frequency trajectories under recurrent "jackpot" events.
• Mathematical modeling to calculate transition densities and understand sampling effects.

Main Results:

• Recurrent "jackpot" events induce a deterministic median bias favoring majority alleles, resembling positive frequency-dependent selection.
• This bias arises from majority alleles sampling deeper into the descendant distribution tail.
• Rare, large frequency increases for minority alleles ensure neutral expectation in the absence of genuine selection.

Conclusions:

• "Jackpot" events generate a fictitious selection force that can be intuitively understood.
• This bias can hinder beneficial mutation establishment, counteract balancing selection, and complicate selection inference from data over short timescales.