Data from: Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains.1_Data_integrationR Script to load input files and collate into a single matched data frame containing fitness, growth rate, and genetic and biolog distance data2_mutation_effect_ANOVAR Script to perform ANOVA to: (i) examine variation in effect of each mutations over strains, (ii) examine variation in average effect of mutations per strain, and (iii) determine average effect of each mutation2a_Recipient strains on Broad phyloR Script to identify engineered strains in context of broader E. coli phylogeny3_PLSregression_&_correlationsScript to perform ANOVA testing for mutation effect variation over different recipient strains and to perform partial least squares (PLS) regression and plot contribution of independent variables to each component4_Phylo_contrastsR script to perform phylogenetic regression and calculate statistics of phylogenetic signalbiologBiolog profiles of engineered strainsfitness_estimatesFitness estimates of engineered strainsgrowth_ratesGrowth rate estimates of parent strain