Quantitative evolutionary dynamics using high-resolution lineage tracking

Sasha F. Levy, Jamie R. Blundell, Sandeep Venkataram, Dmitri A. Petrov, Daniel S. Fisher () and Gavin Sherlock ()
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Sasha F. Levy: Stanford University
Jamie R. Blundell: Stanford University
Sandeep Venkataram: Stanford University
Dmitri A. Petrov: Stanford University
Daniel S. Fisher: Stanford University
Gavin Sherlock: Stanford University

Nature, 2015, vol. 519, issue 7542, 181-186

Abstract: Abstract Evolution of large asexual cell populations underlies ∼30% of deaths worldwide, including those caused by bacteria, fungi, parasites, and cancer. However, the dynamics underlying these evolutionary processes remain poorly understood because they involve many competing beneficial lineages, most of which never rise above extremely low frequencies in the population. To observe these normally hidden evolutionary dynamics, we constructed a sequencing-based ultra high-resolution lineage tracking system in Saccharomyces cerevisiae that allowed us to monitor the relative frequencies of ∼500,000 lineages simultaneously. In contrast to some expectations, we found that the spectrum of fitness effects of beneficial mutations is neither exponential nor monotonic. Early adaptation is a predictable consequence of this spectrum and is strikingly reproducible, but the initial small-effect mutations are soon outcompeted by rarer large-effect mutations that result in variability between replicates. These results suggest that early evolutionary dynamics may be deterministic for a period of time before stochastic effects become important.

Date: 2015
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DOI: 10.1038/nature14279

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