Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose

Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also constrain sequence divergence over evolutionary time scales.

Methods
1. Flow cytometry data of E.coli populations evolved in galactose for 12 days.

Data: EE24.4/8/12 (evolution experiment 24, day 4/8/12) plates 1-3 (delta IS1C - medium C,B,A) + plates 7-10 (IT030 - medium C, B, A; controll plate medium E)
Evolution in galactose (A-1%, B-0.1%, C-0.01%, E - 0%) + 0.1% CASAMINOACIDS.
FlowJo used to export data as scale values into new folder with naming scheme: "ScaleVal_EE24_12C30" (evolution experiment 24_day12 populations_0.01%galactose_strain IT030)
Autogating was used in flow jo to gate the a single concise population of cells (by eye, same within plate, and similar (~60%) for all different plates).

2. amplicon deep sequencing data of E. coli populations evolving in galactose.

Contains random P0 sequences of all evolving pooled populations and R script to generate the plots shown in the figures (Readme)