Format

Send to

Choose Destination
Mol Biol Evol. 2019 Apr 1;36(4):691-708. doi: 10.1093/molbev/msz006.

Shared Molecular Targets Confer Resistance over Short and Long Evolutionary Timescales.

Author information

1
Université Côte d'Azur, CNRS, Inserm, IRCAN, Nice, France.
2
Wellcome Trust Sanger Institute, Cambridge, United Kingdom.
3
Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom.
4
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY.
5
Department of Statistics, Columbia University, New York, NY.
6
Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden.
7
Biozentrum, University of Basel, Basel, Switzerland.
8
Department of Ecology and Evolutionary Biology, University of California, Irvine, CA.
9
Organismal and Evolutionary Biology Research Programme, Department of Computer Science, Institute of Biotechnology, University of Helsinki, Helsinki, Finland.

Abstract

Pre-existing and de novo genetic variants can both drive adaptation to environmental changes, but their relative contributions and interplay remain poorly understood. Here we investigated the evolutionary dynamics in drug-treated yeast populations with different levels of pre-existing variation by experimental evolution coupled with time-resolved sequencing and phenotyping. We found a doubling of pre-existing variation alone boosts the adaptation by 64.1% and 51.5% in hydroxyurea and rapamycin, respectively. The causative pre-existing and de novo variants were selected on shared targets: RNR4 in hydroxyurea and TOR1, TOR2 in rapamycin. Interestingly, the pre-existing and de novo TOR variants map to different functional domains and act via distinct mechanisms. The pre-existing TOR variants from two domesticated strains exhibited opposite rapamycin resistance effects, reflecting lineage-specific functional divergence. This study provides a dynamic view on how pre-existing and de novo variants interactively drive adaptation and deepens our understanding of clonally evolving populations.

KEYWORDS:

adaptation; budding yeast; de novo mutation; drug resistance; pre-existing genetic variation

PMID:
30657986
PMCID:
PMC6445301
[Available on 2020-04-01]
DOI:
10.1093/molbev/msz006

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center