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Adaptive Dynamics During the Early Stages of Clonal Evolution

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Sasha F. Levy, Ph.D.
Group Leader
Joint Initiative for Metrology in Biology (JIMB)
National Institute of Standards and Technology (NIST)
Stanford University

Abstract: 
The adaptive dynamics in large clonally-evolving cell populations are poorly understood, despite having implications for the treatment of cancer and microbial infections. We combine barcode lineage tracking, sequencing of adaptive clones, and mathematical modelling of mutational dynamics to understand the population dynamics during the early stages of experimental evolution. I will show that lineage tracking can be used to discover the both the distribution of beneficial fitness effects and the spectrum of adaptive mutations in experimental evolutions, and that these measures are sufficient to forecast the early dynamics of adaptive diversity. In particular, we find that early adaptive genetic diversity increases predictably, driven by the expansion of many single-mutant lineages. However, a crash in diversity follows, caused by highly-fit double-mutants fed from exponentially growing single-mutants, a process closely related to the classic Luria-Delbruck experiment. The diversity crash is likely to be a general feature of clonal evolution, however its timing and magnitude is stochastic and depends on the population size, the distribution of beneficial fitness effects, and patterns of epistasis.

Status

  • Workflow Status:Published
  • Created By:Jasmine Martin
  • Created:03/27/2018
  • Modified By:Jasmine Martin
  • Modified:03/27/2018