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

Lucile Vigué, Giancarlo Croce, Marie Petitjean, Etienne Ruppé, Olivier Tenaillon () and Martin Weigt ()
Additional contact information
Lucile Vigué: Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME
Giancarlo Croce: University of Lausanne
Marie Petitjean: Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME
Etienne Ruppé: Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME
Olivier Tenaillon: Université Paris Cité and Université Sorbonne Paris Nord, Inserm, IAME
Martin Weigt: Computational and Quantitative Biology—LCQB

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: Abstract Characterizing the effect of mutations is key to understand the evolution of protein sequences and to separate neutral amino-acid changes from deleterious ones. Epistatic interactions between residues can lead to a context dependence of mutation effects. Context dependence constrains the amino-acid changes that can contribute to polymorphism in the short term, and the ones that can accumulate between species in the long term. We use computational approaches to accurately predict the polymorphisms segregating in a panel of 61,157 Escherichia coli genomes from the analysis of distant homologues. By comparing a context-aware Direct-Coupling Analysis modelling to a non-epistatic approach, we show that the genetic context strongly constrains the tolerable amino acids in 30% to 50% of amino-acid sites. The study of more distant species suggests the gradual build-up of genetic context over long evolutionary timescales by the accumulation of small epistatic contributions.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.nature.com/articles/s41467-022-31643-3 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-31643-3

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-022-31643-3

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().