DOI: 10.5061/dryad.6226d
title: Data from: Tempo and mode of genome evolution in a 50,000-generation experiment

description: Adaptation by natural selection depends on the rates, effects and
 interactions of many mutations, making it difficult to determine what
 proportion of mutations in an evolving lineage are beneficial. Here we
 analysed 264 complete genomes from 12 Escherichia coli populations to
 characterize their dynamics over 50,000 generations. The populations that
 retained the ancestral mutation rate support a model in which most fixed
 mutations are beneficial, the fraction of beneficial mutations declines as
 fitness rises, and neutral mutations accumulate at a constant rate. We
 also compared these populations to mutation-accumulation lines evolved
 under a bottlenecking regime that minimizes selection. Nonsynonymous
 mutations, intergenic mutations, insertions and deletions are
 overrepresented in the long-term populations, further supporting the
 inference that most mutations that reached high frequency were favoured by
 selection. These results illuminate the shifting balance of forces that
 govern genome evolution in populations adapting to a new environment.
description: REL606, ancestral
 genomeThis files contains the
 ancestral genome in gff3 formatREL606.gff3REL606 non covered regionsThis file contains the positons in the ancestral genome that are not covered by the short read sequencing technology used due to repeats.REL606.L20.G15.P0.M35.mask.gdLTEE mutator status fileThis files provides information about the point mutator status of each clone. Clones that have an increased point mutation rate have a value of 1 in column 5.LTEE_Mutator_info.txtLTEE mutation fileThis file stores all mutations that were identified in the sequenced genomes of the LTEE, expect the ones in masked regions or in the neighbourhood of IS elements. It is used to compute most mutation analysis.oli.LTEE.final_masked.no_IS_adjacent.tabMAE mutation fileThis file stores all mutations that were identified in the sequenced genomes of the MAE (Mutation Accumulation Experiment), expect the ones in masked regions or in the neighbourhood of IS elements.oli.MAE.final_masked.no_IS_adjacent.tabMAE fitnessThis files contains the fitness estimates of the MAE clones sequenced.MAE_fitness.csvLTEE spectrum countsThis file describes the spectrum of mutations that have accumulated through time in each population of the LTEEspectrum_counts.csvLTEE mutation counts (1)This file describes, for each sequenced clone of the LTEE, the counts of each mutation types recovered. It is used for the genome size figure.count.LTEE.final_masked.csvLTEE mutation counts (2)This file describes, for each sequenced clone of the LTEE, the counts of each mutation types recovered. It is produced by the program ComputeMutationThroughTimeDryad.pl and is used to produce most figures.MutationTypesThroughTime.txtMAE mutation countsThis file describes, for each sequenced clone of the MAE, the counts of each mutation types recovered. It is produced by the program ComputeMutationThroughTimeDryad.pl and is used to produce figures using the MAE as a reference.MutationTypesThroughTimeMAE.txtLTEE point mutation matrix for phylogenyThis file contains an array in which the presence and absence of point mutations recovered in the LTEE sequenced clones is stored as 0 or 1 respectively for each clone. It is produced by ComputeMutationThroughTimeDryad.pl and is used to produce figure 2.MutRArray.txtREL606 ancestral genome compositionThis file, produced by GenomeCompositionComputer.pl, reports the composition of the ancestral genome (synonymous, nonsynonymous, intergenic) for each type of point mutations (AT to CG, AT to GC ...). It is used to compute the expected number of nonsynonymous mutations based on the observed number of synonymous.GenomeComposition.txtComputeMutation command file LTEEThis file is the command file used by ComputeMutationThroughTimeDryad.pl to compute the mutation counts, the mutation matrix. This version is asking for all mutations of the LTEE to be reported.CmdfileLTEE.txtComputeMutation command file MAEThis file is the command file used by ComputeMutationThroughTimeDryad.pl to compute the mutation counts, the mutation matrix. This version is asking for all mutations of the MAE to be reported.CmdfileMAE.txtComputeMutation command file LTEE mutatorThis file is the command file used by ComputeMutationThroughTimeDryad.pl to compute the mutation counts, the mutation matrix. This version is asking to report only mutations occurring in point mutator clones of the LTEECmdfileLTEE_Mutator.txtComputeMutation command file LTEE non mutatorThis file is the command file used by ComputeMutationThroughTimeDryad.pl to compute the mutation counts, the mutation matrix. This version is asking to report only mutations occurring in non point mutator clones of the LTEECmdfileLTEE_nonMutator.txtCompute genome composition perl scriptThis perl script computes the GenomeComposition.txt file that reports the number of synonymous, nonsynonymous and intergenic mutations for each of the 6 types of possible point mutations. See ReadMe.pdf for usage.GenomeCompositionComputer.plFigures R scriptThis R script is used to create all figures and extended data figures. See ReadMe.pdf for usage.ScriptFiguresDryad.rGstat perl scriptThis perl script computes the G stastics of convergence and the randomisation of point mutations used to estimate the p-value of the G estimated. See ReadMe.pdf for usage.ConvergenceGstatDryad.plMAE mutator status fileThis files provides information about the point mutator status of each clone of the MAE. Clones that have an increased point mutation rate have a value of 1 in column 5.MAE_Mutator_info.txtCompute mutation through time perl scriptThis perl script computes the spectrum of mutations found in each clone as well as the matrix used for the phylogeny. See ReadMe.pdf for usage.ComputeMutationThroughTimeDryad.plReadMe fileThis file explains how to use the 4 scripts in order to produce all figures and G scores of the article