Managing AWS instances: Data

Features of the dataset

This dataset was selected for several reasons:

Introduction to the dataset

Microbes are ideal organisms for exploring ‘Long-term Evolution Experiments’ (LTEEs) because thousands of generations can be generated and stored in a way that would be virtually impossible for more complex eukaryotic systems.

In Tenaillon et al 2016, 12 populations of Escherichia coli were propagated for more than 50,000 generations in a glucose-limited minimal medium. This medium was supplemented with citrate which E. coli cannot metabolize in the aerobic conditions of the experiment.

Sequencing of the populations at regular time points reveals that spontaneous citrate-using mutants (Cit+) appeared in a population of E.coli (designated Ara-3) at around 31,000 generations. It should be noted that spontaneous Cit+ mutants are extraordinarily rare - inability to metabolize citrate is one of the defining characters of the E. coli species. Eventually, Cit+ mutants became the dominant population as the experimental growth medium contained a high concentration of citrate relative to glucose.

Around the same time that the Cit+ mutation emerged, another phenotype become prominent in the Ara-3 population. Many Ara-3 E. coli began to develop excessive numbers of mutations, meaning they became hypermutable.

Strains from generation 0 to generation 50,000 were sequenced, including ones that were both Cit+ and Cit- and hypermutable in later generations.

For the purposes of this workshop we’re going to be working with 3 of the sequence reads from this experiment.

SRA Run Number Clone Generation Cit Hypermutable Read Length Sequencing Depth
SRR2589044 REL2181A 5,000 Unknown None 150 60.2
SRR2584863 REL7179B 15,000 Unknown None 150 88
SRR2584866 REL11365 50,000 Cit+ plus 150 138.3

We want to be able to look at differences in mutation rates between hypermutable and non-hypermutable strains. We also want to analyse the sequences to figure out what changes occurred in genomes to make the strains Cit+. Ultimately, we will answer the questions:

References

Tenaillon O, Barrick JE, Ribeck N, Deatherage DE, Blanchard JL, Dasgupta A, Wu GC, Wielgoss S, Cruveiller S, Médigue C, Schneider D, Lenski RE. Tempo and mode of genome evolution in a 50,000-generation experiment (2016) Nature. 536(7615): 165–170. Paper, Supplemental materials

Data available on NCBI SRA and EMBL-EBI ENA.