Deciphering polymorphism in 61,157 Escherichia coli genomes via epistatic sequence landscapes

<p>We use computational models based on Direct Coupling Analysis - DCA - trained on PFAM domains of distant distant homologues to accurately predict the polymorphisms segregating in a panel of 61,157 <em>Escherichia coli </em>genomes.</p> <p>We show that the genetic context (<em>i.e. </em>the rest of the protein sequence) strongly constrains the tolerable amino acids in 30% to 50% of amino-acid sites. Our study also suggests the gradual build-up of genetic context over long evolutionary timescales by the accumulation of small epistatic contributions.</p> <p>Please refer to the README file for additional information on the structure of this dataset.</p> <p>Code to analyse this dataset is available at https://github.com/GiancarloCroce/DCA_polymorphism_Ecoli.</p> <p>&nbsp;</p>