A mutational hotspot that determines highly repeatable evolution can be built and broken by silent genetic changes

James S Horton, Louise M Flanagan, Robert W Jackson, Nicholas K Priest, Tiffany B Taylor

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Abstract

Mutational hotspots can determine evolutionary outcomes and make evolution repeatable. Hotspots are products of multiple evolutionary forces including mutation rate heterogeneity, but this variable is often hard to identify. In this work, we reveal that a near-deterministic genetic hotspot can be built and broken by a handful of silent mutations. We observe this when studying homologous immotile variants of the bacteria Pseudomonas fluorescens, AR2 and Pf0-2x. AR2 resurrects motility through highly repeatable de novo mutation of the same nucleotide in >95% lines in minimal media (ntrB A289C). Pf0-2x, however, evolves via a number of mutations meaning the two strains diverge significantly during adaptation. We determine that this evolutionary disparity is owed to just 6 synonymous variations within the ntrB locus, which we demonstrate by swapping the sites and observing that we are able to both break (>95% to 0%) and build (0% to 80%) a deterministic mutational hotspot. Our work reveals a key role for silent genetic variation in determining adaptive outcomes.

Original languageEnglish
Article number6092
Number of pages10
JournalNature Communications
Volume12
Issue number1
Early online date19 Oct 2021
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Funding Information:
We thank Laurence Hurst for comments on earlier versions of this manuscript. In addition, we thank member of the Taylor lab Matthew Shepherd for insightful comments and discussion, and Mark Silby for contributing the ancestral P. fluorescens Pf0-2x strain used in the study. This work was supported by the University of Bath University Research Studentship Account (URSA) awarded to TBT and NKP; a Royal Society Dorothy Hodgkin Research Fellowship awarded to TBT (DH150169); and the JABBS Foundation for RWJ. Bioinformatics analysis of the paper was carried out using the Medical Research Council’s (MRC) Cloud Infrastructure for Microbial Bioinformatics (CLIMB), and Illumina Whole-Genome Sequencing by the Milner Genomics Centre, Bath, UK and MicrobesNG, Birmingham, UK.

Publisher Copyright:
© 2021, The Author(s).

Keywords

  • Adaptation, Physiological
  • Bacterial Proteins/genetics
  • DNA Mutational Analysis
  • Evolution, Molecular
  • Pseudomonas fluorescens/genetics
  • Silent Mutation

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