Parallel but distinct adaptive routes in the budding and fission yeasts after 10,000 generations of experimental evolution
Experimental evolution has been a useful tool for investigating long-term temporal evolutionary dynamics and molecular mechanisms underlying adaptation. However, extracting fundamental principles and predictive features of evolutionary outcomes from these datasets remains challenging. Here we sought to circumvent these challenges by comparing distant yeast species that share several evolutionary features but differ in evolutionary history and genome architecture, that is Saccharomyces cerevisiae and Schizosaccharomyces pombe. We evolved ten populations of the fission yeast for 10,000 generations in the same conditions as a pre-existing budding yeast dataset, allowing us to observe repeatable evolutionary outcomes within species but diverse molecular targets of adaptation across species. The most frequent route of adaptation was through changes in carbon flux metabolism, which was previously unseen in S. cerevisiae evolved populations, but similar evolutionary paths have been observed in wild populations. This suggests that parallelism is pervasive and that mechanisms of adaptation can be shared among closely related or distant species. Despite similar gene content and identical environments, recurrent adaptation across S. pombe populations involved different genes than in S. cerevisiae and was detectable mostly at the transcriptomic level. This indicates that trans-regulatory effects and contingency may contribute to differences in evolutionary outcomes between these species.
Authors
- Juhee Goyal (ORCID: https://orcid.org/0000-0002-5505-9937)
- Parris T. Humphrey (ORCID: https://orcid.org/0000-0001-5743-1854)
- Julia C. Piper
- Cecilia Trivellin (ORCID: https://orcid.org/0000-0003-4860-9790)
- Tatiana Ruiz-Bedoya (ORCID: https://orcid.org/0000-0002-4858-846X)
- Misha Gupta (ORCID: https://orcid.org/0000-0003-3741-5659)
- Alief Moulana (ORCID: https://orcid.org/0000-0002-0389-7082)
- Arnaud N’Guessan (ORCID: https://orcid.org/0000-0002-3385-725X)
- Tanush Jagdish (ORCID: https://orcid.org/0000-0003-0252-6201)
- Alex N. Nguyen Ba (ORCID: https://orcid.org/0000-0003-1357-6386)
- Katya Kosheleva
- Michael M. Desai (ORCID: https://orcid.org/0000-0002-9581-1150)
- Meghan McDonald
- Christopher W. Bakerlee (ORCID: https://orcid.org/0000-0002-0819-882X)
- Katherine R. Lawrence
- Elizabeth R. Jerison (ORCID: https://orcid.org/0000-0003-3793-8839)
- Milo S. Johnson (ORCID: https://orcid.org/0000-0003-0169-2494)
- Shreyas Gopalakrishnan (ORCID: https://orcid.org/0000-0002-7243-0005)
- Ramya Purkanti (ORCID: https://orcid.org/0000-0003-3199-9753)
- Caroline M. Holmes (ORCID: https://orcid.org/0000-0001-9885-4933)
- Angela M. Phillips (ORCID: https://orcid.org/0000-0002-9806-7574)
- Vivian Wang (ORCID: https://orcid.org/0009-0001-8689-314X)
- S. P. Pai
- Jenya Belousova
- Jiseon Min
- Artur Rego-Costa
- Greta Y.-S. Brenna
- Megan E. Dillingham
Institutions
- Harvard University (US)
- General Electric (Canada) (CA)
- Esri (Canada) (CA)
- Andover Eye Associates (US)
- Quantitative BioSciences (US)
- Cancer Research UK Manchester Institute (GB)
- Alexion Pharma (Switzerland) (CH)
- Monash University (AU)
- Massachusetts Institute of Technology (US)
- Stanford University (US)
Publication Details
- Journal
- Nature Ecology & Evolution
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1038/s41559-026-03017-1
- Primary Topic
- Evolution and Genetic Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Science Foundation
- Harvard University
- National Institutes of Health
- National Defense Science and Engineering Graduate
- Canadian Institutes of Health Research
- Natural Sciences and Engineering Research Council of Canada