Profiling the initial burst of beneficial genetic diversity while rare to anticipate evolution of a cell population

It is important to anticipate evolution in many situations relevant to human health, including during tumor progression and over the course of chronic microbial infections. One may want to diagnose whether a disease is likely to develop in ways that are harmful and which treatments will be most effective in preventing its spread or progression. In this study we used deep-sequencing and error correction methods to profile rare variants that evolved in a model E. coli population in order to understand to what extent profiling these variants could allow one to predict the longer-term course of evolution.