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Is phenotypic evolution predictable?

A quantitative theory of evolution must include an understanding of how genetic changes alter an organism phenotypically.  Advances in sequencing have illuminated genomic evolution, but the complexities of the genotype to phenotype map make evolutionary dynamics unpredictable. 


However, recent work (e.g. PNAS, 2013) suggests that phenotypic diversity can be constrained to low-dimensional phenotypic spaces.  Constraints in phenotypic variation may provide a route to making microevolutionary dynamics predictable.  However, to achieve this we need to understand how genomic changes relate to the space of possible phenotypes and how selection results in adaptation.


We are using motility in Escherichia coli as a model system to understand the dynamics of phenotypic evolution at the genomic, single-cell and population levels.  We have developed a simple technique to evolve E. coli for faster migration through porous media.


Recent work (eLife, 2017) has shown precisely how genetic architecture interacts with phenotypic constraints to determine evolutionary trajectories.   We find that cells selected for faster migration either swim faster and grow slower, or grow faster and swim slower. 

In this study we exploited high-throughput single-cell tracking to make precise measurements of motility.

Previous work used information theoretic techniques to quantify behavioral variation in microbes and to understand how the structure of phenotypic variation related to the chemical environment of the cell. (PNAS, 2013)


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