Phenotype inference in an Escherichia coli strain panel.

Abstract:

:Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Combining high-throughput gene function assays with mechanistic models of the impact of genetic variants is a promising alternative to genome-wide association studies. Here we have assembled a large panel of 696 Escherichia coli strains, which we have genotyped and measured their phenotypic profile across 214 growth conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across all strains. Finally, we combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to compute the growth defects of each strain. Not only could we reliably predict these defects in up to 38% of tested conditions, but we could also directly identify the causal variants that were validated through complementation assays. Our work demonstrates the power of forward predictive models and the possibility of precision genetic interventions.

journal_name

Elife

journal_title

eLife

authors

Galardini M,Koumoutsi A,Herrera-Dominguez L,Cordero Varela JA,Telzerow A,Wagih O,Wartel M,Clermont O,Denamur E,Typas A,Beltrao P

doi

10.7554/eLife.31035

subject

Has Abstract

pub_date

2017-12-27 00:00:00

issn

2050-084X

pii

31035

journal_volume

6

pub_type

杂志文章

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