Larger Numbers Can Impede Adaptation in Asexual Populations despite Entailing Greater Genetic Variation
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Periodic bottlenecks play a major role in shaping the adaptive dynamics of natural and laboratory populations of asexual microbes. Here we study how they affect the ‘Extent of Adaptation’ (EoA), in such populations. EoA, the average fitness gain relative to the ancestor, is the quantity of interest in a large number of microbial experimental-evolution studies which assume that for any given bottleneck size (N0) and number of generations between bottlenecks (g), the harmonic mean size (HM = N0g) will predict the ensuing evolutionary dynamics. However, there are no theoretical or empirical validations for HM being a good predictor of EoA. Using experimental-evolution with Escherichia coli and individual-based simulations, we show that HM fails to predict EoA (i.e., higher N0g does not lead to higher EoA). This is because although higher g allows populations to arrive at superior benefits by entailing increased variation, it also reduces the efficacy of selection, which lowers EoA. We show that EoA can be maximized in evolution experiments by either maximizing N0 and/or minimizing g. We also conjecture that N0/g is a better predictor of EoA than N0g. Our results call for a re-evaluation of the role of population size in predicting fitness trajectories. They also aid in predicting adaptation in asexual populations, which has important evolutionary, epidemiological and economic implications.
KeywordsPopulation size Experimental evolution Extent of adaptation Population bottlenecks Adaptive size
We thank Milind Watve, M.S. Madhusudhan, Shraddha Karve and Sachit Daniel for their invaluable suggestions and insightful discussions. We thank Amitabh Joshi for critical comments on an earlier draft of the manuscript. Y.D.C. was supported by a Senior Research Fellowship, initially sponsored by the Indian Institute of Science Education and Research, Pune, and later by the Council for Scientific and Industrial Research (CSIR), Government of India. S.I.A. thanks the Department of Science and Technology (DST), Government of India for financial support through a KVPY fellowship. This project was supported by an external grant from Department of Biotechnology, Government of India and internal funding from Indian Institute of Science Education and Research, Pune.
This study was funded by Department of Biotechnology, Ministry of Science and Technology (Grant No. BT/PR5655/BRB/10/1088/2012).
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Conflict of interest
The authors declare that they have no conflict of interest.
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