PT - JOURNAL ARTICLE AU - Marco Galardin AU - Alexandra Koumoutsi AU - Lucia Herrera-Dominguez AU - Juan Antonio Cordero Varela AU - Anja Telzerow AU - Omar Wagih AU - Morgane Wartel AU - Olivier Clermont AU - Erick Denamur AU - Athanasios Typas AU - Pedro Beltrao TI - Phenotype prediction in an <em>Escherichia coli</em> strain panel AID - 10.1101/141879 DP - 2017 Jan 01 TA - bioRxiv PG - 141879 4099 - http://biorxiv.org/content/early/2017/05/24/141879.short 4100 - http://biorxiv.org/content/early/2017/05/24/141879.full AB - Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Here, we set to predict fitness defects of an individual using mechanistic models of the impact of genetic variants combined with prior knowledge of gene function. We assembled a diverse panel of 696 Escherichia coli strains for which we obtained genomes and measured growth phenotypes in 214 conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across strains. We combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to predict the strains’ growth defects, providing significant predictions for up to 38% of tested conditions. The putative causal variants were validated in complementation assays highlighting commonly perturbed pathways in evolution for the emergence of growth phenotypes. Altogether, our work illustrates the power of integrating high-throughput gene function assays to predict the phenotypes of individuals.HighlightsAssembled a reference panel of E. coli strainsGenotyped and high-throughput phenotyped the E. coli reference strain panelReliably predicted the impact of genetic variants in up to 38% of tested conditionsHighlighted common genetic pathways for the emergence of deleterious phenotypes