LB 17-180 - Experimental evidence metapopulation structure accelerates adaptation

Thursday, August 18, 2022

5:00 PM – 6:30 PM EDT

Located in: ESA Exhibit Hall

Presenting Author(s)

PC

Partha Chakraborty

PhD student
University of Ottawa, Ontario, Canada

Coauthor(s)

LN

Louis Nemzer

Nova Southeastern University, Florida, United States
RK

Rees Kassen

University of Ottawa, Canada

Background/Question/Methods:

Most natural populations are spatially structured, meaning they exist as a collection of smaller populations distributed in space and connected by migration pathways. Calculations based on standard population genetic models of dispersal predict little effect of spatial structure on the fixation probability (Pfix), the likelihood a given mutation increases in frequency to become present in all surviving individuals. In contrast, evolutionary graph theory (EGT) predicts certain topologies amplify (increase) the probability that a beneficial mutation will spread in the population, relative to a well-mixed population. Direct experimental tests of the role of network topology on the rate of adaptation are lacking.

Results/Conclusions:

Here, through both experiment and simulation, we show that star-shaped topologies involving bidirectional dispersal between a central hub and peripheral leaves can be amplifiers of selection relative to a well-mixed network, consistent with the predictions of EGT. We further show that the mechanism responsible for amplification is the reduced probability that a rare beneficial mutant will be lost due to drift when it encounters a new patch. We also show the importance of the migration rate, which is not independently adjustable in most previous models. Our results provide the first empirical support for the prediction of EGT that spatial structure can amplify the spread of a beneficial mutation and broaden the conditions under which this phenomenon is thought to occur. More generally, our work shows how the interplay between spatial structure and evolutionary forces determine the fate of a beneficial mutation and underscoring the importance of spatial structure in governing diverse phenomena such as the spread of drug resistance factors or invasive species. It also points the way toward using network topology to amplify the effects of weakly favoured mutations under directed evolution in industrial applications.